Radiographic image analysis device and method, and storage medium having stored therein program

ABSTRACT

A subject image is acquired. A virtual model of the subject having a predetermined body thickness distribution is acquired. A composite image of an estimated primary X-ray image, which is obtained by estimating a primary X-ray image of the virtual model obtained by radiography from the virtual model, and an estimated scattered X-ray image, which is obtained by estimating a scattered X-ray image of the virtual model obtained by radiography from the virtual model, is generated as an estimated image which is obtained by estimating a radiographic image of the subject obtained by radiography. The body thickness distribution of the virtual model is corrected such that a difference between the estimated image and the subject image is reduced. The corrected body thickness distribution of the virtual model is determined as the body thickness distribution of the subject.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of PCT International Application No.PCT/JP2014/003802 filed on Jul. 17, 2014, which claims priority under 35U.S.C. §1.19(a) to Japanese Patent Application No. 2013-159528 filed onJul. 31, 2013 and Japanese Patent Application No. 2013-229941 filed onNov. 6, 2013. Each of the above applications is hereby expresslyincorporated by reference, in its entirety; into the presentapplication.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to an image analysis device and method anda storage medium having stored therein a program which analyze aradiographic image of a subject obtained by radiography; and moreparticularly, to an image analysis device and method and a program whichanalyze a radiographic image of a subject obtained by radiography toestimate the thickness of the subject at each position of theradiographic image.

2. Description of the Related Art

It is known that, when a radiographic image of the subject is capturedwith radiation passing through the subject, the influence of thescattering of radiation or a reduction in the transmissivity ofradiation in the subject increases as the thickness of the subjectincreases, which results in a change in the quality of the acquiredradiographic image. Therefore, a technique has been proposed whichroughly estimates the thickness of the subject, on the basis of variouskinds of information, such as imaging conditions, a signal value of aradiographic image, the histogram width of the signal value of theradiographic image, and the length of the subject in the subject imagein a predetermined direction and changes the conditions of imageprocessing, such as a process of removing scattered X-rays of thecaptured radiographic image, or imaging conditions applied to thecapture of the radiographic image, on the basis of the estimatedthickness of the subject.

For example, JP1990-244881A (JP-H02-244881A) discloses a method whichmeasures the pixel value of an image of a simulated subject with a knownthickness, which is captured by radiography under known imagingconditions, prepares an association table in which the body thickness isassociated with the pixel value in advance, estimates a rough bodythickness distribution according to the pixel value of the subjectimage, on the basis of the association table, estimates a scatteredX-ray component of the subject image corresponding to the body thicknessdistribution of the subject image, and subtracts the scattered X-raycomponent from the subject image to acquire a processed image.

Trotter et al., “Thickness-dependent Scatter Correction Algorithm forDigital Mammography”, Proc. SPIE Vol. 4682, May 2002, pp. 469-478discloses a method which estimates a scattered X-ray component of aradiographic image on the basis of a thickness distribution of the humanbody and removes the scattered X-ray component. According to the imageprocessing method disclosed in Trotter and four others,“Thickness-dependent Scatter Correction Algorithm for DigitalMammography”, Proc. SHE Vol. 4682, May 2002, pp. 469-478, an estimatedscattered X-ray image obtained by applying a predetermined function toan input subject image and estimating an image of a scattered X-rayincluded in the subject image is generated on the basis of the bodythickness distribution estimated from the pixel value of the subjectimage and the estimated scattered X-ray image is subtracted from thesubject image to generate an estimated primary X-ray image obtained byestimating a primary X-ray image from the input subject image. Inaddition, a process of applying a predetermined function to thegenerated estimated primary X-ray image to generate an estimatedscattered X-ray image and subtracting the estimated scattered X-rayimage from the subject image to generate an estimated primary X-rayimage is repeated until the estimated scattered X-ray image is convergedunder predetermined convergence conditions, the converged estimatedscattered X-ray image is calculated, and the estimated scattered X-rayimage is subtracted from the subject image to finally acquire aprocessed image from which the scattered X-ray component has beenremoved. In addition, Trotter and four others, “Thickness-dependentScatter Correction Algorithm for Digital Mammography”, Proc. SPIE Vol.4682, May 2002, pp. 469-478 discloses a method which adjusts apredetermined function for estimating the image of the scattered X-rayincluded in the subject image on the basis of the body thickness.

SUMMARY OF THE INVENTION

Here, in order to calculate a detailed body thickness in which theinternal structure of the subject, such as the lung field in thesubject, is reflected, it is preferable to calculate the thickness ofthe subject from the pixel value of the subject image of the subjectwhich is actually captured. However, the subject image includes acomponent of the primary X-ray (primary X-ray component) which passesthrough the subject and is directly emitted to the radiation detectorand a component of the scattered X-ray (scattered X-ray component) whichis generated by the scattering of radiation in the subject.

Therefore, when the method for estimating the body thickness on thebasis of the pixel value is applied to the radiographic image which iscaptured without using a scattered X-ray removal grid (grid) as inJP1990-244881A (JP-H02-244881A) or Trotter and four others,“Thickness-dependent Scatter Correction Algorithm for DigitalMammography”, Proc. SPIE Vol, 4682, May 2002, pp. 469-478, it isdifficult to accurately estimate the body thickness distribution of thesubject due to the influence of the scattered X-ray component in theradiographic image. In addition, it is considered that the subject imageis captured using a grid in order to avoid the influence of thescattered X-ray component. However, there is a demand for accuratelyestimating the body thickness distribution from the subject image whichis captured without using a grid, in order to reduce a burden such asthe radiation dose received by the subject.

The invention has been made in view of the above-mentioned problems andan object of the invention is to perform an image analysis process whichanalyzes a radiographic image captured by irradiating a subject withradiation to accurately estimate a body thickness distribution of thesubject.

According to an aspect of the invention, there is provided aradiographic image analysis device that analyzes a subject image of asubject obtained by radiography to estimate a body thicknessdistribution of the subject. The radiographic image analysis deviceincludes: an image acquisition unit that acquires the subject image; avirtual model acquisition unit that acquires a virtual model of thesubject having a predetermined body thickness distribution; an estimatedimage generation unit that generates a composite image of an estimatedprimary X-ray image, which is obtained by estimating a primary X-rayimage of the virtual model obtained by radiography from the virtualmodel, and an estimated scattered X-ray image, which is obtained byestimating a scattered X-ray image of the virtual model obtained byradiography from the virtual model, as an estimated image which isobtained by estimating a radiographic image of the subject obtained byradiography; a correction unit that corrects the body thicknessdistribution of the virtual model such that a difference between theestimated image and the subject image is reduced; and a body thicknessdistribution determination unit that determines the corrected bodythickness distribution of the virtual model as the body thicknessdistribution of the subject.

According to another aspect of the invention, there is provided aradiographic image analysis method that is performed in a radiographicimage analysis device and analyzes a subject image which is obtained byirradiating a subject with radiation to estimate a body thicknessdistribution of the subject. The radiographic image analysis methodincludes: an image acquisition step of acquiring the subject image; avirtual model acquisition step of acquiring a virtual model of thesubject having a predetermined body thickness distribution; an estimatedimage generation step of generating a composite image of an estimatedprimary X-ray image, which is obtained by estimating a primary X-rayimage of the virtual model obtained by radiography from the virtualmodel, and an estimated scattered X-ray image, which is obtained byestimating a scattered X-ray image of the virtual model obtained byradiography from the virtual model, as an estimated image which isobtained by estimating a radiographic image of the subject obtained byradiography; a correction step of correcting the body thicknessdistribution of the virtual model such that a difference between theestimated image and the subject image is reduced; and a body thicknessdistribution determination step of determining the corrected bodythickness distribution of the virtual model as the body thicknessdistribution of the subject.

In addition, a program may be provided which causes a computer toperform the radiographic image analysis method according to theabove-mentioned aspect of the invention.

The “body thickness” means the sum of the thicknesses of subject regionsother than air regions on an emitted radiation path.

The “estimated image” may be substantially regarded as a composite imageof an estimated primary X-ray image, which is obtained by estimating aprimary X-ray image of the virtual model obtained by radiography fromthe virtual model, and an estimated scattered X-ray image, which isobtained by estimating a scattered X-ray image of the virtual modelobtained by radiography from the virtual model. For example, anestimated primary X-ray image generation function may be applied to thevirtual model to generate the estimated primary X-ray image, anestimated scattered X-ray image generation function may be applied tothe virtual model to generate the estimated scattered X-ray image, andthe images may be combined with each other. in addition, an estimatedimage generation function may be applied to the virtual model toestimate the estimated image.

In the radiographic image analysis device according to theabove-mentioned aspect of the invention, preferably, the virtual modelacquisition unit further acquires the virtual model having the correctedbody thickness distribution, the estimated image generation unit furthergenerates the estimated image from the virtual model having thecorrected body thickness distribution, and the correction unit furthercorrects the body thickness distribution of the virtual model such thata difference between the generated estimated image and the subject imageis reduced.

In this case, preferably, when the difference between the estimatedimage and the subject image is equal to or less than a predeterminedthreshold value, the body thickness distribution determination unitdetermines the body thickness distribution of the virtual model as thebody thickness distribution of the subject.

In the radiographic image analysis device according to theabove-mentioned aspect of the invention, the correction unit may correctthe body thickness distribution of the virtual model such that the sumof absolute values of pixel values of a difference image between theestimated image and the subject image or the sum of the squares of thepixel values of the difference image is reduced.

In the radiographic image analysis device according to theabove-mentioned aspect of the invention, the correction unit may changethe body thickness distribution of the virtual model for each partialregion including one or more pixels in the virtual model, calculate abody thickness of the partial region at which the difference between theestimated image and the subject image is reduced, and correct the bodythickness distribution of the virtual model using the calculated bodythickness of each partial region.

In the invention, the “predetermined body thickness distribution” is notnecessarily similar to the body thickness distribution of the subjectand may be any body thickness distribution. For example, when thesubject is a predetermined part of the human body, the predeterminedbody thickness distribution may be the body thickness distribution ofthe same part of a human body different from the subject or thepredetermined body thickness distribution may be a uniform distribution.

In the radiographic image analysis device according to theabove-mentioned aspect of the invention, the predetermined bodythickness distribution may be created by acquiring a comparative subjectimage of a comparative subject different from the subject, which isobtained by radiography, and a three-dimensional image of thecomparative subject obtained by three-dimensional imaging, and measuringa body thickness of the comparative subject on a straight linecorresponding to a radiation path of the comparative subject image ateach position of the acquired three-dimensional image.

In the radiographic image analysis device according to theabove-mentioned aspect of the invention, preferably, the virtual modelfurther includes characteristic information indicating at least one ofstructures included in the virtual model, the arrangement of thestructures, and characteristics of the structures with respect toradiation, and the estimated image generation unit selects a parameterfor calculating the estimated image according to the structurecorresponding to each position of the virtual model, on the basis of thecharacteristic information, and generates the estimated image.

In the radiographic image analysis device according to theabove-mentioned aspect of the invention, preferably, the estimated imagegeneration unit acquires characteristic information indicatingstructures included in the subject image, the arrangement of thestructures, and characteristics of the structures with respect toradiation as the characteristic information of the virtual model,selects a parameter for calculating the estimated image according to thestructure corresponding to each position of the virtual model, on thebasis of the characteristic information, and generates the estimatedimage.

The “characteristic information” may be specified by any method as longas it indicates the structures included in the image, the arrangement ofthe structures, and the characteristics of the structures with respectto radiation. For example, the characteristic information can be definedby the anatomic structures to be captured, such as the lung field, bone,blood vessel, and organ of the subject, and the composition of eachanatomic structure.

Preferably, the radiographic image analysis device according to theabove-mentioned aspect of the invention further includes: a scatteredX-ray information acquisition unit that acquires scattered X-rayinformation which is obtained by estimating a scattered X-ray of thesubject image, using the determined body thickness distribution of thesubject; and a scattered X-ray removal unit that performs a process ofremoving the scattered X-ray of the subject image on the basis of theacquired scattered X-ray information.

In the above-mentioned aspects of the invention, the subject image maybe captured without using a scattered X-ray removal grid.

According to the invention, the subject image is acquired. The virtualmodel of the subject having a predetermined body thickness distributionis acquired. The composite image of the estimated primary X-ray image,which is obtained by estimating the primary X-ray image of the virtualmodel obtained by radiography from the virtual model, and the estimatedscattered X-ray image, which is obtained by estimating the scatteredX-ray image of the virtual model obtained by radiography from thevirtual model, is generated as the estimated image which is obtained byestimating the radiographic image of the subject obtained byradiography. The body thickness distribution of the virtual model iscorrected such that the difference between the estimated image and thesubject image is reduced. The corrected body thickness distribution ofthe virtual model is determined as the body thickness distribution ofthe subject. According to this structure, it is possible to correct thebody thickness distribution on the basis of the difference between theestimated image and the subject image such that the estimated image isclose to the subject image. Therefore, since the corrected bodythickness distribution of the virtual model is determined as the bodythickness distribution of the subject, it is possible accuratelydetermine the body thickness distribution of the subject image.

In addition, the virtual model acquisition unit further acquires thevirtual model having the corrected body thickness distribution, theestimated image generation unit further generates the estimated imagefrom the virtual model having the corrected body thickness distribution,and the correction unit further corrects the body thickness distributionof the virtual model such that the difference between the generatedestimated image and the subject image is reduced, In this case, theprocess of correcting the body thickness distribution on the basis ofthe virtual model having the corrected body thickness distribution isrepeatedly performed to accurately correct the body thicknessdistribution such that the estimated image is close to the subjectimage. Since the corrected body thickness distribution of the virtualmodel is determined as the body thickness distribution of the subject,it is possible to more accurately determine the body thicknessdistribution of the subject image.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram schematically illustrating the structure of aradiography system to which a radiographic image analysis deviceaccording to a first embodiment of the invention is applied.

FIG. 2 is a flowchart illustrating a process performed by theradiographic image analysis device according to the first embodiment ofthe invention.

FIG. 3 is a diagram illustrating an example of an association table of abody thickness distribution.

FIG. 4A is a diagram illustrating an example of an estimated imagegeneration method.

FIG. 4B is a diagram illustrating another example of the estimated imagegeneration method.

FIG. 5 is a block diagram schematically illustrating the structure of aradiography system to which a radiographic image analysis deviceaccording to a third embodiment of the invention is applied.

FIG. 6 is a flowchart illustrating a process performed by theradiographic image analysis device according to the third embodiment ofthe invention.

FIG. 7 is a flowchart illustrating a process performed by a radiographicimage analysis device according to a fourth embodiment of the invention.

FIG. 8 is a flowchart illustrating a process performed by a radiographicimage analysis device according to a fifth embodiment of the invention,

DESCRIPTION OF THE PREFERRED EMBODIMENTS

Hereinafter, embodiments of the invention will be described withreference to the drawings. FIG. 1 is a block diagram schematicallyillustrating the structure of a radiography system to which aradiographic image analysis device according to a first embodiment ofthe invention is applied. As illustrated in FIG. 1, the radiographysystem according to this embodiment includes an imaging device 10, acontrol device 20 which controls the system, and an image analysisdevice 30 (radiographic image analysis device).

The imaging device 10 includes an X-ray source 12 which irradiates asubject K with X-rays and a radiation detector 14 which detects X-rayspassing through the subject K and acquires a radiographic image of thesubject K. In this embodiment, a scattered X-ray removal grid (grid) forremoving X-rays which are scattered by the subject K among the X-rayspassing through the subject K is not provided between the subject K andthe radiation detector 14.

The control device 20 includes an X-ray source driving control unit 22which controls the driving of the X-ray source 12 according to setimaging conditions and a detector control unit 24 which controls theradiation detector 14 such that the radiographic image (subject image)of the subject is acquired and stores the radiographic image in astorage unit 42.

The image analysis device 30 includes an image acquisition unit 31 whichacquires a captured subject image Ik of the subject K from, for example,the detector control unit 24 or the storage unit 42, which will bedescribed below, a virtual model acquisition unit 32 which acquires avirtual model M of the subject K having an initial body thicknessdistribution T₀ (predetermined body thickness distribution), anestimated image generation unit 33 which generates a composite image ofan estimated primary X-ray image Ip, which is obtained by estimating aprimary X-ray image of the virtual model obtained by radiography fromthe virtual model M, and an estimated scattered X-ray image Is, which isobtained by estimating a scattered X-ray image of the virtual modelobtained by radiography from the virtual model M, as an estimated imageIm which is obtained by estimating the radiographic image of the subjectK. obtained by radiography, a correction unit 34 which corrects theinitial body thickness distribution T₀ of the virtual model M such thatthe difference between the estimated image Iii and the subject image Ikis reduced, on the basis of the estimated image Im and the subject imageIk, a body thickness distribution determination unit 35 which determinesthe corrected body thickness distribution T_(n−1) (n is a naturalnumber) as a body thickness distribution Tk of the subject image Ik, ascattered X-ray information acquisition unit 36 which acquires scatteredX-ray information indicating a scattered X-ray component of the X-rayincluded in the subject image Ik on the basis of the determined bodythickness distribution Tk(x, y), a scattered X-ray removal unit 37 whichperforms a process of removing the scattered rays of the subject imageIk acquired by the radiation detector 14 on the basis of the scatteredX-ray information acquired by the scattered X-ray informationacquisition unit 36, an input unit 38, a display unit 40, and a storageunit 42 which includes storage media, such as a memory and a hard disk,and stores various kinds of information. The input unit 38 receivesvarious inputs of the operator to the image analysis device 30.Specifically, the input unit 38 is, for example, a keyboard, a mouse, ora touch panel. The display unit 40 is, for example, a CRT display or aliquid crystal display and assists the display of the radiographic imageacquired by the imaging device 10 and various inputs required for ascattered X-ray removal process which will be described below.

The image acquisition unit 31, the virtual model acquisition unit 32,the estimated image generation unit 33, the correction unit 34, the bodythickness distribution determination unit 35, the scattered X-rayinformation acquisition unit 36, the scattered X-ray removal unit 37,the input unit 38, the display unit 40, and the storage unit 42 can beformed by a computer system such as a general personal computer.

The image analysis device 30 analyzes the subject image Ik which hasbeen captured by the irradiation of the subject K, who is the person tobe examined, with radiation to estimate the body thickness distributionTk of the subject K.

The storage unit 42 of the image analysis device 30 stores imagingconditions such as the subject image Ik acquired by the detector controlunit 24, the radiography dose thereof, a tube voltage, a distance SIDbetween the X-ray source 12 and a detection surface of the radiationdetector 14, materials forming the object to be irradiated by the X-raysource and a filter, the type of radiation detector used forradiography, and an air gap (the distance from the subject to theradiation detector). An association table LUT in which a concentrationvalue (pixel value) and a body thickness are associated with each otherfor each of a plurality of imaging conditions is created in advance andis stored in the storage unit 42. In addition, the storage unit 42stores the virtual model M of the subject K having the initial bodythickness distribution T₀(x, y). It is assumed that various parametersrequired for each process and the generated images (for example, theestimated primary X-ray image and the estimated scattered X-ray image)are appropriately stored in the storage unit 42. In the specification,the body thickness means the sum of the thicknesses of subject regionsexcept for an air region on the path of the emitted radiation. In thisembodiment, the detector control unit 24 acquires the imaging conditionsand stores the imaging conditions in the storage unit 42. However, theX-ray source driving control unit 22 may acquire the imaging conditionsand store the imaging conditions in the storage unit 42.

Next, the flow of a radiographic image analysis process performed by theimage analysis device 30 according to this embodiment will be describedwith reference to the flowchart illustrated in FIG. 2.

First, the image acquisition unit 31 acquires the subject image Ik of apatient, who is the subject K, obtained by radiography from the storageunit 42 (S01).

Then, the virtual model acquisition unit 32 acquires the virtual model Mof the subject K having the initial body thickness distribution T₀(x, y)from the storage unit 42 (S02). The virtual model M is data whichvirtually indicates the subject K having the initial body thicknessdistribution T₀(x, y) in which the body thickness is associated witheach position on an x-y plane. Structures (here, anatomic structuressuch as a lung field, a bone, and an organ) included in the virtualmodel M, the arrangement of the structures, and characteristicinformation indicating, for example, the characteristics of thestructures with respect to radiation are set on the basis of thearrangement and composition of anatomic structures, such as the lungfield of the chest and abdomen of a comparative subject and the bones inthe vicinity thereof.

The virtual model M may have any initial body thickness distributionT₀(x, y). However, in this embodiment, the initial body thicknessdistribution T₀ is generated and acquired by the virtual modelacquisition unit 32. The virtual model acquisition unit 32 acquires theimaging conditions, such as the radiography dose of the subject K, atube voltage, and an SID, and acquires an association table LUT in whichthe pixel value corresponding to the imaging conditions of the subject Kis associated with the body thickness from the storage unit 42. FIG. 3illustrates an example of the table LUT in which the pixel value isassociated with the body thickness. Then, the virtual model acquisitionunit 32 acquires the image data of the comparative subject (human body)obtained by radiography from the storage unit 42 and specifies the bodythickness corresponding to the value of each pixel in the image data ofthe comparative subject on the basis of the association table LUT toacquire a body thickness distribution of the image data of thecomparative subject. Then, the virtual model acquisition unit 32acquires the body thickness distribution of the image data as theinitial body thickness distribution T₀ (predetermined body thicknessdistribution) of the virtual model M. The initial body thicknessdistribution T₀ may be generated during the process of acquiring thevirtual model M as in this embodiment, or may be set before the processof acquiring the virtual model M.

T ₀=(x,y)=LUT(I _(k)(x,y))   (1)

Then, the estimated image generation unit 33 combines the estimatedprimary X-ray image Ip, which is obtained when the image of the virtualmodel M is captured under the same imaging conditions as the subjectimage, and the estimated scattered X-ray image Is, which is obtainedwhen the image of the virtual model M is captured under the same imagingconditions as the subject image, to generate the estimated image Im(S03). FIGS. 4A and 4B are diagrams illustrating a method for generatingthe estimated image Im.

As illustrated in FIG. 4A, the estimated image generation unit 33generates the estimated primary X-ray image Ip, which is obtained whenthe image of the virtual model M is captured under the same imagingconditions as the subject image Ik, according to the followingExpression (2), and generates the estimated scattered X-ray image Isusing the generated estimated primary X-ray image Ip, according to thefollowing Expression (3). Then, the estimated image generation unit 33combines the estimated primary X-ray image Ip and the estimatedscattered X-ray image Is to generate the estimated image Im, as shown inthe following Expression (4) (S03). When the estimated primary X-rayimage Ip and the estimated scattered X-ray image Is are generated first,the initial body thickness distribution T₀(x, y) is used in EstimationExpressions (2) and (3) (n is I in Expressions (2) and (3)).

$\begin{matrix}{{I_{p}\left( {x,y} \right)} = {{I_{o}\left( {x,y} \right)} \times {\exp \left( {{- {T_{n - 1}\left( {x,y} \right)}} \times \mu} \right)}}} & (2) \\{{I_{s}\left( {x,y} \right)} = {\sum\limits_{x^{\prime},y^{\prime}}^{\;}{{I_{p}\left( {x^{\prime},y^{\prime}} \right)}{K_{s}\left( {x,y,{T_{n - 1}\left( {x^{\prime},y^{\prime}} \right)},\theta_{x^{\prime},y^{\prime}}} \right)}}}} & (3) \\{{I_{m}\left( {x,y} \right)} = {{I_{p}\left( {x,y} \right)} + {I_{s}\left( {x,y} \right)}}} & (4)\end{matrix}$

Here, (x, y) is the coordinates of a pixel position of the subject imageIk, Ip(x, y) is an estimated primary X-ray image at the pixel position(x, y), Is(x, y) is an estimated scattered X-ray image at the pixelposition (x, y), Io(x, y) is a dose at the pixel position (x, y), Im(x,y) is an estimated image at the pixel position (x, y), μ is a linearattenuation coefficient of the subject, and K_(s)(x, y, Tn(x′, y′),θ_(x′, y′)) is a convolution kernel indicating a point spread functioncorresponding to the thickness of the subject at the pixel position (x,y). The dose Io(x, y) is a radiation dose which is detected by adetector on the assumption that no subject is present and variesdepending on the distance (SID) between the X-ray source 12 and thedetection surface of the radiation detector 14, a tube voltage, and aradiography dose. In addition, Oθ_(x′, y)′ indicates a parameter whichis specified by the imaging conditions, such as the tube voltage, or thecharacteristic information of the virtual model M.

In addition, the estimated image Im may be an image which is estimatedto be obtained when the radiographic image of the virtual model M iscaptured and may be any image which is substantially regarded as acomposite image of the estimated primary X-ray image Ip and theestimated scattered X-ray image Is. For example, as illustrated in FIG.4B, the estimated image Im may be generated by the convolution integralof the kernel combining a primary X-ray component and a scattered X-raycomponent, using the following Expression (5), instead of Expressions(2) to (4). Here, K_(p+s)(x, y, T_(n−1)(x′, y′), θ_(x′, y′)) is a kernelindicating a point spread function that combines the primary X-raycomponent and the scattered X-ray component. In addition, any modelfunction may be used as long as it can generate an estimated imageobtained by combining the estimated primary radiation image and theestimated scattered X-ray image from the image obtained by radiography.

$\begin{matrix}{{I_{m}\left( {x,y} \right)} = {\sum\limits_{x^{\prime},y^{\prime}}^{\;}{K_{p + s}\left( {x,y,{T_{n - 1}\left( {x^{\prime},y^{\prime}} \right)},\theta_{x^{\prime},y^{\prime}}} \right)}}} & (5)\end{matrix}$

The next process will be described with reference to the flowchartillustrated in FIG. 2. Then, the body thickness distributiondetermination unit 35 determines whether the difference between thesubject image Ik and the estimated image Im satisfies end conditions(S04). Here, an error value T_(error) indicating the difference betweenthe subject image Ik and the estimated image Im is defined as shown inthe following Expression (6) and Expression (7). It is determinedwhether the error value V_(error) is equal to or less than a thresholdvalue as the end conditions. As shown in Expression (7), the sum of thesquares of each pixel value of a difference image Id which is obtainedby subtracting the estimated image Im from the subject image Ik isdefined as the error function f_(error). In addition, any determinationmethod may be used as long as it can determine whether or not thedifference between the subject image Ik and the estimated image Im issmall enough to be allowable, as the end conditions.

$\begin{matrix}{V_{error} = {f_{error}\left( {{I_{m}\left( {x,y} \right)},{I_{k}\left( {x,y} \right)}} \right)}} & (6) \\{{f_{error}\left( {{I_{m}\left( {x,y} \right)},{I_{k}\left( {x,y} \right)}} \right)} = {\sum\limits_{x,y}^{\;}\left( {{I_{m}\left( {x,y} \right)} - {I_{k}\left( {x,y} \right)}} \right)^{2}}} & (7)\end{matrix}$

However, the invention is not limited to the above-mentioned example.For example, the error function f_(error) can be defined by any methodwhich can indicate the difference between the subject image Ik and theestimated image Im. For example, as shown in the following Expression(8), the sum of the absolute values of each pixel value of adifferential image Id obtained by subtracting the estimated image Imfrom the subject image Ik may be defined as the error functionf_(error).

$\begin{matrix}{{f_{error}\left( {{I_{m}\left( {x,y} \right)},{I_{k}\left( {x,y} \right)}} \right)} = {\sum\limits_{x,y}^{\;}{{{I_{m}\left( {x,y} \right)} - {I_{k}\left( {x,y} \right)}}}}} & (8)\end{matrix}$

When the error value V_(error) does not satisfy the end conditions (S04,No), the correction unit 34 performs a correction process of correctinga body thickness distribution T_(n−1) (the initial body thicknessdistribution T₀ when n is 1) (S05).

Any method which can acquire the correction value of each position inthe body thickness distribution T_(n−1) such that the difference betweenthe subject image Ik and the estimated image Im is reduced can beapplied in order to perform the process of correcting the body thicknessdistribution T_(n−1). In this embodiment, a. process is performed whichchanges the body thickness distribution T_(n−1) of the virtual model Mfor each partial region including one or more pixels in the virtualmodel M to calculate the body thickness of the partial region where thedifference between the estimated image Im and the subject image Ik issmall. Then, the body thickness distribution of the virtual model iscorrected by the calculated body thickness of each partial region.

Specifically, in this embodiment, it is assumed that the correctionvalue of the body thickness with the body thickness distribution T_(n−1)is calculated using the steepest descent method. It is possible tominimize the output value of the error function f_(error) by repeatedlycalculating dT_(n−1)(x, y) on the basis of the primary partialdifferential (gradient) of the error function f_(error) while changingonly the body thickness at one specific coordinate point in T_(n−1)(x,y) among the pixels of the virtual model M, using the followingExpressions (9) and (10). Then, the body thickness at one specificcoordinate point when the output value of the error function f_(error)is minimized is determined as the correction value of the body thicknessat the coordinate point. For the other pixels, similarly, the correctionvalue of each body thickness is calculated and the body thicknessdistribution of each pixel is corrected. In this way, a corrected bodythickness distribution Tn is acquired.

$\begin{matrix}\begin{matrix}{\mspace{79mu} {{T_{n}\left( {x,y} \right)} = {{T_{n - 1}\left( {x,y} \right)} - {\alpha \; {{T_{n - 1}\left( {x,y} \right)}}}}}} \\{= {{T_{n - 1}\left( {x,y} \right)} - {\alpha \; \frac{}{{T_{n - 1}\left( {x,y} \right)}}f_{error}}}}\end{matrix} & (9) \\{{\frac{}{{T_{n - 1}\left( {x,y} \right)}}f_{error}} = {\sum\limits_{x^{\prime},y^{\prime}}^{\;}{\left( {{I_{m}\left( {x^{\prime},y^{\prime}} \right)} - {I_{k}\left( {x^{\prime},y^{\prime}} \right)}} \right)\frac{}{{T_{n - 1}\left( {x,y} \right)}}{K_{p + s}\left( {x^{\prime},y^{\prime},{T_{n - 1}\left( {x,y} \right)},\theta_{x,y}} \right)}}}} & (10) \\{{\frac{}{{T_{n - 1}\left( {x,y} \right)}}{K_{p + s}\left( {x^{\prime},y^{\prime},{T_{n - 1}\left( {x,y} \right)},\theta_{x,y}} \right)}} = {{K_{p + s}\left( {x^{\prime},y^{\prime},{{T_{n - 1}\left( {x,y} \right)} + {t}},\theta_{x,y}} \right)} - {K_{p + s}\left( {x^{\prime},y^{\prime},{T_{n - 1}\left( {x,y} \right)},\theta_{x,y}} \right)}}} & (11)\end{matrix}$

However, in Expression (9), α is an update coefficient which is aparameter indicating the update speed of the body thickness. As anexample of a method for calculating a differential value portion ofK_(p+s) shown in Expression (10), for example, a value change when avery small value dt is added to T_(n−1)(x, y) can be calculated byExpression (11) and can be used as the value of K_(p+s) in theExpression (10). In Expressions (1) to (12), the same components aredenoted by the same reference numerals and the description thereof willnot be repeated. Any optimization method can be applied as long as itcan minimize the error value V_(error) indicating the difference betweenthe subject image Ik and the estimated image Im. For example, a simplexmethod, the steepest descent method, or a conjugate gradient method canbe used.

When the corrected body thickness distribution T_(n) is acquired, thebody thickness distribution determination unit 35 increases the value ofn by 1 to update the value of n (n=n+1) and the virtual modelacquisition unit 32 acquires the corrected body thickness distributionT_(n) (S02). Then, the estimated image generation unit 33 and the bodythickness distribution determination unit 35 perform the process in S03and S04 for the acquired body thickness distribution T_(n) using thesame method as described above. Then, similarly, the process ofcorrecting the body thickness distribution T_(n) (S05), the process ofacquiring the virtual model M having the corrected body thicknessdistribution T_(n) (S02), the process of generating a new estimatedimage Im using the body thickness distribution T_(n) (S03), and theprocess of determining whether the difference between a newly generatedestimated image Im and the subject image Ik satisfies the end conditions(S04) are repeatedly performed until the error value V_(error)indicating the difference between the subject image Ik and the estimatedimage Im satisfies the end conditions.

On the other hand, if it is determined that the error value V_(error)satisfies the end conditions (S04, Yes), the body thickness distributiondetermination unit 35 determines the body thickness distribution T_(n)used for the error value V_(error) the end conditions are satisfied asthe body thickness distribution Tk of the subject image Ik and ends theimage analysis process according to this embodiment (S06).

In this embodiment, when an instruction to perform a scattered X-rayremoval process for the subject image Ik is received from the user afterthe body thickness distribution determination process (S06) illustratedin FIG. 3, a scattered Xray information acquisition process and thescattered X-ray removal process are performed as optional functions ofthe image analysis device 30. Here, the scattered X-ray informationacquisition unit 36 applies the acquired body thickness distribution Tk,acquires an estimated primary X-ray image of the subject image Ikaccording to Expression (2), and acquires an estimated scattered X-rayimage Is(x, y) of the subject image Ik(x, y) according to Expression(3). Then, the scattered X-ray removal unit 37 subtracts the estimatedscattered X-ray image Is(x, y) of the subject image Ik from the subjectimage Ik(x, y) to generate a processed image from which the influence ofscattered rays has been removed and stores the processed image in thestorage unit 42. The processed image is appropriately displayed on thedisplay unit 40 in response to an instruction from the user. In thedetermination of the end conditions (S04), when the error valueV_(error) satisfies the end conditions, the difference between thesubject image Ik and the estimated image Im is small enough to beallowable and the difference between the estimated primary X-ray imageIp and the primary X-ray image of the subject image Ik is also small.Therefore, when the user wants to acquire the processed image, fromwhich the scattered rays have been removed, from the subject image Ik,the estimated primary X-ray image Ip used to calculate the error value Vsatisfying the end conditions may be acquired as the primary X-ray imageof the subject image Ik, that is, a processed image after the process ofremoving scattered rays from the subject image Ik.

According to this embodiment, the estimated primary X-ray image Ip andthe estimated scattered X-ray image Is of the virtual model M which areestimated to be obtained by radiography are combined to generate theestimated image Im and the body thickness distribution of the virtualmodel M is corrected such that the difference between the estimatedimage Im and the subject image Ik is reduced. Therefore, it is possibleto accurately correct the body thickness distribution T_(n) on the basisof the difference between the estimated image Im and the subject imageIk such that the estimated image Im is close to the subject image Ik.The corrected body thickness distribution T_(n) of the virtual model Mis used as the body thickness distribution Tk of the subject K, whichmakes it possible to accurately determine the body thicknessdistribution Tk of the subject image Ik. In the method according to therelated art, the influence of the scattered X-ray component is large inthe image which is captured without using a grid and it is difficult toaccurately calculate the body thickness distribution from the image. Incontrast, the method according to this embodiment accurately correctsthe body thickness distribution T_(n) such that the estimated image Imis close to the subject image Ik and determines the corrected bodythickness distribution as the body thickness distribution Tk of thesubject K, Therefore, even when the subject image Ik is captured withoutusing a grid, it is possible to more accurately obtain the bodythickness distribution Tk than the method according to the related art.

In addition, as described in this embodiment, the virtual modelacquisition unit 32 further acquires the virtual model M having thecorrected body thickness distribution T_(n) and the estimated imagegeneration unit 33 further generates the estimated image Im from thevirtual model M having the corrected body thickness distribution T_(n).When further correcting the body thickness distribution T_(n) of thevirtual model M such that the difference between the generated estimatedimage Im and the subject image Ik is reduced, the correction unit 34repeatedly performs the process of correcting the body thicknessdistribution T on the basis of the virtual model having the correctedbody thickness distribution T_(n) to accurately correct the bodythickness distribution T such that the estimated image Im is close tothe subject image Ik. Therefore, since the corrected body thicknessdistribution T_(n+1) of the virtual model M is used as the bodythickness distribution Tk of the subject K, it is possible to accuratelydetermine the body thickness distribution Tk of the subject image Ik.

As described in this embodiment, when the difference between theestimated image Im and the subject image Ik is small enough to beallowable, the body thickness distribution determination unit 35determines the body thickness distribution T_(n) of the virtual model Mas the body thickness distribution Tk of the subject K. in this case,the body thickness distribution is repeatedly corrected such that theestimated image Im is close to the subject image Ik. Therefore, it ispossible to very accurately determine the body thickness distribution ofthe subject image. In addition, the body thickness distributiondetermination unit 35 determines whether or not the difference betweenthe estimated image Im and the subject image Ik is equal to or less thanthe threshold value. Therefore, the body thickness distributiondetermination unit 35 appropriately determines whether the differencebetween the estimated image Im and the subject image Ik is small enoughto be allowable and repeatedly corrects the body thickness distributionsuch that the estimated image Im is close to the subject image Ik. As aresult, it is possible to very accurately determine the body thicknessdistribution of the subject image.

In this embodiment, the correction unit 34 corrects the body thicknessdistribution of the virtual model such that the sum of the absolutevalues of the pixel values of a difference image between the estimatedimage and the subject image or the sum of the squares of the pixelvalues of the difference image is reduced. Therefore, it is possible toappropriately determine the magnitude of the difference between theestimated image Im and the subject image Ik.

As described in this embodiment, the correction unit 34 changes the bodythickness of one partial region in the body thickness distributionT_(n−1) of the virtual model M for each partial region including one ormore pixels in the virtual model M and calculates the body thickness ofthe one part when the difference between the estimated image Im and thesubject image Ik is minimized. In addition, the correction unit 34corrects the body thickness distribution of the virtual model M usingthe calculated body thickness of each part. Therefore, it is possible toaccurately calculate the correction value of the body thickness of eachpixel and to acquire an appropriately corrected body thicknessdistribution T_(n).

According to this embodiment, the image analysis device includes thescattered X-ray information acquisition unit 36 which acquires scatteredX-ray information obtained by estimating the scattered rays of thesubject image using the determined body thickness distribution Tk of thesubject K and the scattered X-ray removal unit 37 which performs theprocess of removing the scattered rays of the subject image on the basisof the acquired scattered X-ray information. Therefore, it is possibleto acquire a processed image subjected to the scattered X-ray removalprocess with high accuracy.

In a second embodiment of the invention, the estimated image generationunit 33 may acquire structures included in the subject image Ik, thearrangement of the structures, and characteristic information indicatingthe characteristics of the structures with respect to radiation as thecharacteristic information of the virtual model M, select parameters forcalculating the estimated image Im according to the structurecorresponding to each position of the virtual model M, on the basis ofthe characteristic information, and generate the estimated image Im. Forexample, it is considered that, as shown in the following Expression(12), the linear attenuation coefficient in Expression (2) when theestimated primary X-ray image Ip is generated from the virtual model Musing Expression (2) is changed at each position depending on thestructures (the composition of the structure), on the basis of thecharacteristic information, and is then used. In a radiographic image, aprimary X-ray component or a scattered X-ray component is complexlychanged at each position on the radiographic image, depending on thestructures included in the subject, such as the bone of the subject, thekind of organ, and a cavity included in the organ, and the spatialposition of the structures. Therefore, when the characteristicinformation of the subject image Ik is acquired as the characteristicinformation of the virtual model M and the parameters used for, forexample, the estimated primary X-ray image or the estimated scatteredX-ray image are appropriately selected according to the structure(virtually) included at each position of the virtual model M, it ispossible to reduce errors of the primary X-ray component or thescattered X-ray component caused by the structure and to accuratelygenerate the estimated primary X-ray image Ip and the estimatedscattered X-ray image Is.

$\begin{matrix}{{\mu \left( {x,y} \right)} = \left\{ \begin{matrix}{\mu_{bone}\mspace{11mu} {when}\mspace{14mu} a\mspace{14mu} {bone}\mspace{14mu} {is}\mspace{14mu} {present}\mspace{14mu} {at}\mspace{14mu} {the}\mspace{14mu} {position}} \\{\mu_{lung}\mspace{14mu} {when}\mspace{14mu} {the}\mspace{14mu} {lung}\mspace{14mu} {is}\mspace{14mu} {present}\mspace{14mu} {at}\mspace{14mu} {the}\mspace{14mu} {position}} \\{\mu_{soft}\mspace{14mu} {when}\mspace{14mu} a\mspace{14mu} {soft}\mspace{14mu} {tissue}\mspace{14mu} {is}\mspace{14mu} {present}\mspace{14mu} {at}\mspace{14mu} {the}\mspace{14mu} {position}}\end{matrix} \right.} & (12)\end{matrix}$

For the parameter θ_(x′, y′) in Expression (3), different values ofθ_(x′, y′) may be set for each structure and θ_(x′, y′) applied to eachposition may vary depending on the structure at each position. Inaddition, a three-dimensional image, such as a CT image or an MRI imageof the same subject K as that in the subject image Ik, may be acquired,and the characteristic information of the subject image Ik may bemeasured and acquired from the acquired CT image or MRI image. Whencharacteristic information is acquired using the three-dimensional imageof the same subject K, it is possible to accurately acquire informationsuch as the spatial position of the organ or the bone.

Various body thickness distributions may be used as the initial bodythickness distribution (predetermined body thickness distribution). Forexample, the initial body thickness distribution may be a uniformdistribution. However, it is preferable to use the body thicknessdistribution which is estimated to be close to the subject K to acertain extent as the initial body thickness distribution in terms of acalculation load. From this point of view, for example, it is preferablethat the body thickness distribution T previously measured for the samesubject K is used as the initial body thickness distribution T₀. In thiscase, it is possible to determine the body thickness distribution onlyby finely correcting a difference in the subject K due to a posture or achange over time and to reduce a calculation. load.

In addition, the initial body thickness distribution T₀ may be createdby acquiring a comparative subject image of a comparative subjectdifferent from the subject, which is obtained by radiography, and athree-dimensional image, such as a CT image or an MRI image obtained bya three-dimensional imaging process for the comparative subject, and bymeasuring the body thickness of the comparative subject on a straightline corresponding to a radiation path in the comparative subject imageat each position on the acquired three-dimensional image. The use of thethree-dimensional image makes it possible to obtain an accurate initialbody thickness distribution. Therefore, it is possible to determine thebody thickness distribution only by finely correcting, for example, theposture of the subject and thus to reduce a calculation load.

When the body thickness distribution of the comparative subject isprepared, the following is considered: a plurality of sets of the bodythickness distribution of each comparative subject and physiqueinformation indicating the physique of the comparative subject areprepared for a plurality of comparative subjects; the physiqueinformation of the subject is acquired; the body thickness distributionof the comparative subject having the physique information similar tothe physique information of the subject is specified; and the specifiedbody thickness distribution of the comparative subject is used as theinitial body thickness distribution T_(o) of the subject image, In thiscase, since the body thickness distribution of the comparative subjecthaving a similar physique to the subject is used as the initial bodythickness distribution, the initial body thickness distribution islikely to be similar to the body thickness distribution of the subjectand it is possible to determine the body thickness distribution only byfinely correcting, for example, the posture of the subject and thus toreduce a calculation load. In addition, the physique information of thesubject and the physique information of the comparative subject may beinput by the user, or may be physique information extracted from thesubject image and the comparative subject, such as the width of theconcentration histogram of each of the subject image and theradiographic image of the comparative subject (the difference betweenthe maximum value and the minimum value of a concentration value).Furthermore, any physique information may be used as long as it can beextracted from the subject image and the comparative subject. Forexample, the length of a predetermined part of the subject may be usedas the physique information of the subject.

In addition, for example, the following method may be used: before andafter the radiographic image of the subject is captured, the distancebetween the detector and the surface of the subject close to the X-raysource is measured by a measurement device, such as an ultrasonic sensoror a digital measurement device capable of measuring a distance; themeasured value is acquired from, for example, the measurement device orthe input of the user; and the acquired distance between the bodysurface of the subject and the detector is used as an index value fordetermining the initial body thickness distribution. In this case, forexample, the distance between the body surface of the subject and thedetector can be used as the physique information of the subject. Inaddition, the initial body thickness distribution may be a uniformdistribution of the distance between the body surface of the subject andthe detector.

Various methods which can generate the estimated primary X-ray image Ipand the estimated scattered X-ray image Is may be applied. For example,instead of Expressions (2) and (3), for example, a Monte Carlosimulation method may be used to generate the estimated primary X-rayimage Ip and the estimated scattered X-ray image Is, as described, inKato Hideki, “A New Method for Eliminating Scatter Components from aDigital X-ray Image by Later Processing”, Japanese Journal ofRadiological Technology, Vo. 62, No. 9, September 2006, p.1359-1368. Inaddition, when the Monte Carlo simulation method is used, it ispreferable to use characteristic information which is informationindicating structures included in the virtual model M, the arrangementof the structures, and the characteristics of the structures withrespect to radiation. In this case, it is possible to generate theestimated primary X-ray image Ip and the estimated scattered X-ray imageIs with higher accuracy.

In each of the above-described embodiments, the image analysis devicemay further include a imaging condition acquisition unit which acquiresthe actual imaging conditions that are considered to be used. The tubevoltage, the radiography dose, and the distance SID between the X-raysource and the detector are changed depending on, for example, the bodytype of the subject, the purpose of diagnosis, or the environment of thefacilities in which the radiography system is installed, Therefore,preferably; the imaging condition acquisition unit acquires the imagingconditions of the subject image Ik and the estimated image generation.unit 33 selects a parameter (for example, θ_(x′, y′) in Expressions (3)and (5)), which is used to generate the estimated image Im and variesdepending on the imaging conditions, on the basis of the acquiredimaging conditions and performs the process of generating the estimatedimage Im (S03) using the selected parameter.

The imaging condition acquisition unit may acquire the imagingconditions using any method as long as it can acquire the imagingconditions. For example, the imaging condition acquisition unit mayacquire the imaging conditions which are input by the user or theimaging conditions which are calculated from the pixel value detected bythe detector at the position where no subject is present. In this case,a table in which the concentration value of a void region, which is aregion in which no subject is present, is associated with a radiographydose may be stored in the storage unit 42 and the radiography dose maybe acquired with reference to the table on the basis of theconcentration value of the void region. In addition, the imagingcondition acquisition unit can use various methods which can acquire theimaging conditions actually applied to the capture of the subject image.

For example, the imaging condition acquisition unit may acquire thedistance SID between the X-ray source and the surface of the detectorusing any method. For example, the imaging condition acquisition unitcan acquire, as the SID, the distance between the X-ray source and thedetector measured by a measurement device capable of measuring thedistance, such as an ultrasonic sensor or a digital measure. Inaddition, the imaging condition acquisition unit may acquire aradiographic image of a three-dimensional marker which is arranged atthe position that is a known distance away from the radiation detector14 between the X-ray source 12 and the radiation detector 14 and analyzethe position of the three-dimensional marker or a scattered X-raycomponent in the radiographic image to calculate the SID.

The imaging condition acquisition unit may acquire the radiography doseusing any method. For example, the imaging condition acquisition unitmay acquire a dose which is measured by a measurement device, such as anarea dosimeter, as the radiography dose incident on the radiationdetector 14. In addition, the imaging condition acquisition unit maycapture the image of an acrylic model with a known thickness togetherwith the image of the subject and acquire a radiography dose on thebasis of the concentration of the acrylic model in the acquiredradiographic image. In this case, a table in which the concentration ofthe acrylic model is associated with the radiography dose may be storedin the storage unit 42 and the radiography dose may be acquired withreference to the table on the basis of the concentration of the acrylicmodel. In many cases, the imaging conditions are determined according tothe facilities in which the radiography system is installed. Therefore,when the imaging conditions are unclear in the actual radiography, it ispreferable to use the imaging conditions corresponding to thefacilities.

The pixel value of the subject image Ik is likely to vary depending onthe type of radiation detector 14. Preferably, information forspecifying the type of radiation detector 14 is included in the imagingconditions and a dose specification table in which a concentration value(pixel value) that is measured in advance is associated with a dose thatreaches the radiation detector 14 is made for each combination of theradiography dose, the tube voltage, the SID, and the type of radiationdetector 14 in advance and is then stored in the storage unit 42. Inthis case, the imaging condition acquisition unit may acquire the typeof radiation detector 14 used to capture the subject image Ik, specify adose corresponding to a concentration value at each position withreference to the dose specification table corresponding to the acquiredtype of radiation detector 14, and use the specified dose as theradiography dose.

Preferably, the correction unit 34 selects a parameter (for example,θ_(x′, y′) in Expressions (10) and (11)), which is used to generate theestimated image Im and varies depending on the imaging conditions, onthe basis of the acquired imaging conditions and performs the process ofcorrecting the body thickness distribution of the estimated image Im(S05) using the selected parameter. In this case, it is possible toappropriately set the parameter which varies depending on the imagingconditions according to the imaging conditions of the subject image Ikand to generate the estimated image Im. Therefore, it is possible toaccurately estimate and generate the estimated image Im. As a result, itis possible to accurately determine the body thickness distribution ofthe subject K.

In each of the above-described embodiments, the image acquisition unit31 acquires the subject image Ik which is captured without using a grid.However, the invention is not limited thereto. The image acquisitionunit 31 may acquire, as the subject image Ik, an image obtained byperforming a process of removing a fringe caused by a grid for theradiographic image of the subject K which has been captured using thegrid. The process of removing the fringe caused by the grid may beperformed using various methods capable of removing the fringe caused bythe grid. For example, the method disclosed in JP2012-203504A can bereferred to.

When the image acquisition unit 31 acquires, as the subject image Ik,the image obtained by performing the process of removing the fringecaused by the grid for the radiographic image of the subject K which hasbeen captured using the grid, it is preferable that a table in whichscattered X-ray transmissivity Ts and primary X-ray transmissivity Tpare associated with each other for each grid information item forspecifying the type of grid is made in advance and is then stored in thestorage unit 42. In this case, it is preferable that the estimated imagegeneration unit 33 specifies scattered X-ray transmissivity Ts^(k) andprimary X-ray transmissivity Tp^(k) corresponding to grid informationwhich is used to capture the image of the subject, on the basis of thetable in which the scattered X-ray transmissivity Ts and the primaryX-ray transmissivity Tp are associated with each grid information item,and generates the estimated image, using the following ConditionalExpression (4-1) instead of Condition Expression (4). In this case, theabsorption of primary rays by the same type of grid as that used tocapture the subject image can be reflected in the estimated primaryX-ray image of the virtual model and the absorption of scattered X-raysby the same type of grid as that used to capture the subject image canbe reflected in the estimated scattered X-ray image of the virtualmodel. As such, since the absorption of the scattered X-rays and theprimary X-rays by the same type of grid is reflected in the estimatedimage on the basis of the grid used to capture the subject image, it ispossible to reduce errors in the body thickness distribution due to theabsorption of radiation to the grid used to capture the subject image.The grid information can be any combination of a grid ratio, griddensity, information indicating whether the grid is a convergence typeor a parallel type, a focusing distance when the grid is a convergencetype, and one or more elements included in an interspace material (forexample, aluminum, fiber, or Bakelite).

I _(m)(x, y)=I _(p)(x, y)×T _(p) ^(k) +I _(s)(x, y)×T _(s) ^(k)   (4-1)

Next, a third embodiment of the invention will be described withreference to FIGS. 5 and 6. FIG. 5 is a block diagram schematicallyillustrating the structure of a radiography system to which aradiographic image analysis device according to the third embodiment ofthe invention is applied. FIG. 6 is a flowchart illustrating a processperformed by the radiographic image analysis device according to thethird embodiment of the invention.

As illustrated in FIG. 5, the image analysis device 30 according to thethird embodiment includes a scattered X-ray analysis unit 43 whichperforms image processing for a subject image acquired by radiographywithout using a grid such that the same scattered X-ray removal effectas that of when the subject image is actually captured using the grid isobtained. The scattered X-ray analysis unit 43 includes a characteristicacquisition unit 39 which will be described below, the scattered X-rayinformation acquisition unit 36, and the scattered X-ray removal unit37. The image analysis device 30 according to the third embodimentdiffers from the image analysis device 30 according to each of theabove-described embodiments in that it further includes thecharacteristic acquisition unit 39 that acquires virtual gridcharacteristics which are the characteristics of a virtual grid, thescattered X-ray information acquisition unit 36 further acquiresscattered component information indicating a scattered component of anX-ray included in the subject image Ik as scattered X-ray information,and the scattered X-ray removal unit performs a process of removingscattered X-rays in the subject image acquired by the radiation detector14, on the basis of the virtual grid characteristics acquired by thecharacteristic acquisition unit 39 and the scattered componentinformation acquired by the scattered X-ray information acquisition unit36. The image analysis device 30 according to the third embodiment hasthe same components as the image analysis device 30 illustrated in FIG.1 and the functions and processes of each component are substantiallythe same as those in the above-described embodiments except for theabove-mentioned difference. Therefore, the description is focused on thedifference from the first embodiment and the description of the samecomponents will not be repeated.

The characteristic acquisition unit 39 acquires the virtual gridcharacteristics which are input by the operator through the input unit38. In the third embodiment, the virtual grid characteristics are thescattered X-ray transmissivity is of the virtual grid and thetransmissivity (primary X-ray transmissivity) Tp of the primary X-rayswhich pass through the subject K and are directly emitted to theradiation detector 14. The scattered X-ray transmissivity Ts and theprimary X-ray transmissivity Tp have a value in the range of 0 to 1.

The characteristic acquisition unit 39 may directly receive the valuesof the scattered X-ray transmissivity Ts and the primary X-raytransmissivity Tp and acquire the virtual grid characteristics. In thethird embodiment, the characteristic acquisition unit 39 receives atleast one of grid information indicating the type of grid, information(subject information) about the subject, and imaging conditions when thesubject image Ik is acquired, which are designated by the operator, andacquires the virtual grid characteristics, that is, the scattered X-raytransmissivity Ts and the primary X-ray transmissivity Tp. Hereinafter,the imaging conditions used in the characteristic acquisition unit 39are referred to as imaging conditions for acquiring characteristics.

Here, the grid information includes at least one of information itemsfor specifying the type of grid, such as a grid ratio, grid density,information indicating whether the grid is a convergence type or aparallel type, a focusing distance when the grid is a convergence type,and an interspace material (for example, aluminum, fiber, or Bakelite).The scattered X-ray transmissivity Ts and the primary X-raytransmissivity Tp vary depending on the type of grid. Therefore, for thegrid information, a table in which at least one of various kinds of gridinformation is associated with the virtual grid characteristics isstored in the storage unit 42.

The subject information includes the type of subject such as the chest,the abdomen, and the head, Here, when the subject image Ik is captured,the type of grid used is generally determined according to the part tobe captured by radiography, and the scattered X-ray transmissivity Tsand the primary X-ray transmissivity Tp vary depending on the type ofgrid. Therefore, for the subject information, a table in which variouskinds of subject information are associated with the virtual gridcharacteristics is stored in the storage unit 42.

The imaging conditions for acquiring characteristics include at leastone of a source to image-receptor distance (SID) during radiography, aradiography dose, a tube voltage, materials forming the target of theX-ray source and a filter, and the type of radiation detector used forradiography. Here, when the subject image Ik is captured, the type ofgrid used is generally determined according to the imaging conditionsand the scattered X-ray transmissivity Ts and the primary X-raytransmissivity Tp vary depending on the type of grid. Therefore, for theimaging conditions for acquiring characteristics, a table in whichvarious imaging conditions for acquiring characteristics are associatedwith the virtual grid characteristics is stored in the storage unit 42.The imaging conditions for acquiring characteristics may be the same asimaging conditions used to determine the body thickness distribution(imaging conditions for determining the body thickness distribution) orimaging conditions for acquiring scattered X-ray information which areused to acquire scattered X-ray information, which will be describedbelow, as long as they include parameters required to acquire thevirtual grid characteristics, or may be different from these imagingconditions.

The characteristic acquisition unit 39 acquires the virtual gridcharacteristics with reference to the table stored in the storage unit42, on the basis of at least one of the grid information, the subjectinformation, and the imaging conditions for acquiring characteristicswhich are input from the input unit 38. In addition, it is preferablethat the grid information, the subject information, and the imagingconditions for acquiring characteristics are directly input through theinput unit 38. For example, the following structure may be used: a listof various kinds of grid information, various kinds of subjectinformation, and various imaging conditions for acquiringcharacteristics is displayed on the display unit 40; and when theoperator selects at least one of the grid information, the subjectinformation, and the imaging conditions for acquiring characteristicsfrom the list, the grid information, the subject information, and theimaging conditions for acquiring characteristics are input.

In the third embodiment, the scattered X-ray removal process isperformed by performing frequency decomposition for the subject imageIk, which will be described below In the third embodiment, the virtualgrid characteristics are acquired for each of a plurality of frequencybands of the subject image Ik obtained by frequency decomposition.Therefore, the virtual grid characteristics in the above-mentioned tableare associated with each of the plurality of frequency bands.

In addition, a table in which all of the grid information, the subjectinformation, and the imaging conditions for acquiring characteristicsare associated with the virtual grid characteristics may be stored inthe storage unit 42 and the virtual grid characteristics may be acquiredon the basis of all of the grid information, the subject information,and the imaging conditions for acquiring characteristics. In this case,the table is at least a four-dimensional table in which various kinds ofgrid information, various kinds of subject information, various imagingconditions for acquiring characteristics, and virtual gridcharacteristics are associated with each other.

An exposure factor which is the rate of increase in an irradiation dosewhich is increased by the use of the grid, a contrast improvementcoefficient which is the ratio of contrast when the grid is used andwhen the grid is not used, and selectivity which is the ratio of primaryX-ray transmissivity to scattered X-ray transmissivity arecharacteristic values indicating the characteristics of the grid. It ispossible to calculate the scattered X-ray transmissivity Ts and theprimary X-ray transmissivity Tp from these characteristic values.Therefore, the characteristic acquisition unit 39 may receive at leastone of the exposure factor, the contrast improvement coefficient, andthe selectivity which are designated by the operator and calculate andacquire the virtual grid characteristics, that is, the scattered X-raytransmissivity Ts and the primary X-ray transmissivity Tp.

In the third embodiment, the image analysis device 30 performs thescattered X-ray removal process on the basis of scattered componentinformation, in addition to the virtual grid characteristics. Therefore,the scattered X-ray information acquisition unit 36 further acquires thescattered component information as the scattered X-ray information. Inthe third embodiment, the scattered component information is a scatteredX-ray content distribution of the subject image Ik in which, when thesubject K is, for example, the chest, the amount of scattered X-ray islarge in a central portion of the subject image Ik in which amediastinum is present and is small in a peripheral portion in which thelung field is present.

The scattered X-ray information acquisition unit 36 analyzes the subjectimage Ik acquired by radiography to acquire the scattered componentinformation, that is, the scattered X-ray content distribution. Thesubject image Ik is analyzed on the basis of irradiation fieldinformation, subject information, and imaging conditions when thesubject image Ik is captured.

The irradiation field information is information indicating anirradiation field distribution related to the position and magnitude ofan irradiation field included in the subject image Ik when radiographyis performed using an irradiation field stop. The subject information isinformation related to, for example, the position of the subject on thesubject image Ik, the composition distribution of the subject, the sizeof the subject, and the thickness of the subject, in addition to thetype of subject, such as a chest, abdomen, or head. The imagingconditions used in the scattered X-ray information acquisition unit 36are information related to, for example, a radiography dose (a tubecurrent×an irradiation time), a tube voltage, a source to image-receptordistance (SID) during radiography, an air gap (the distance from thesubject to the radiation detector), and the characteristics of theradiation detector. Hereinafter, the imaging conditions used in thescattered X-ray information acquisition unit 36 are referred to asimaging conditions for acquiring scattered X-ray information. Theimaging conditions for acquiring scattered X-ray information may be thesame as the imaging conditions used to determine the body thicknessdistribution or the imaging conditions for acquiring characteristics, aslong as they include parameters required to acquire the scattered X-rayinformation, or may be different from these imaging conditions.

The irradiation field information, the subject information, and theimaging conditions for acquiring scattered X-ray information are factorsfor determining the distribution of the scattered X-rays included in thesubject image Ik. For example, the amount of scattered X-rays depends onthe size of the irradiation field. The amount of scattered X-raysincreases as the thickness of the subject increases and decreases as agap between the subject and the radiation detector increases. Therefore,it is possible to accurately acquire the scattered X-ray contentdistribution using these information items.

The scattered X-ray information acquisition unit 36 calculates a primaryX-ray image and a scattered X-ray image from the body thicknessdistribution Tk(x, y) of the subject K on the basis of the followingExpressions (13) and (14) and calculates a scattered X-ray contentdistribution S(x, y) from the calculated primary X-ray image andscattered X-ray image on the basis of the following Expression (15).Here, the scattered X-ray content distribution S(x, y) has a value inthe range of 0 to 1.

Ip(x, y)=Io(x, y)×exp(−Tk(x, y)×μ)   (13)

Is(x, y)=Io(x, y)*Sσ(Tk(x, y))   (14)

S(x, y)=Is(x, y)/(Is(x, y)+Ip(x, y))   (15)

In the above-mentioned expressions, (x, y) is the coordinates of a pixelposition of the subject image Ik, Ip(x, y) is a primary X-ray image atthe pixel position (x, y), Is(x, y) is a scattered X-ray image at thepixel position (x, y), Io(x, y) is a radiation dose which is incident onthe surface of the subject at the pixel position (x, y), μ is a linearattenuation coefficient of the subject, and Sσ (Tk(x, y)) is aconvolution kernel indicating scattering characteristics correspondingto the thickness of the subject at the pixel position (x, y). Theabove-mentioned Expressions (2) and (13) are based on a knownexponential attenuation law and Expression (14) is based on the methoddisclosed in “J M Boon et al, An analytical model of the scatteredradiation distribution in diagnostic radiology, Med. Phys, 15 (5),September/October 1988” (Reference Literature 1). In Expressions (13)and (14), the incident radiation dose Io(x, y) on the surface of thesubject is cancelled by division when S(x, y) is calculated even if itis defined as any value. Therefore, the incident dose Io(x, y) may haveany value. For example, the incident dose Io(x, y) is 1.

Here, “*” in Expression (14) is an operator indicating a convolutionoperation. The nature of the kernel varies depending on, for example, anirradiation field distribution, the composition distribution of thesubject, an irradiation dose during radiography; a tube voltage, thesource to image-receptor distance, an air gap, and the characteristicsof the radiation detector, in addition to the thickness of the subject.According to the method described in Reference Literature 1, thescattered X-ray can be approximated by the convolution of the pointspread function (Sσ(x, y) in Expression (14)) with respect to theprimary X-ray. In addition, Sσ(Tk(x, y)) can be experimentallycalculated on the basis of, for example, the irradiation fieldinformation, the subject information, and the imaging conditions foracquiring scattered X-ray information.

In the third embodiment, Sσ(Tk(x, y)) may be calculated on the basis ofthe irradiation field information, the subject information, and theimaging conditions for acquiring scattered X-ray information duringradiography. In addition, a table in which various kinds of irradiationfield information, various kinds of subject information, various imagingconditions for acquiring scattered X-ray information, and Sσ(Tk(x, y))are associated with each other may be stored in the storage unit 42 andSσ(Tk(x, y)) may be calculated with reference to the table on the basisof the irradiation field information, the subject information, and theimaging conditions for acquiring scattered X-ray information duringradiography. Furthermore, Sσ(Tk(x, y)) may be approximated by Tk(x, y).

The scattered X-ray removal unit 37 performs the scattered X-ray removalprocess of reducing a frequency component in a frequency band that isregarded as the scattered X-ray in the subject image Ik, on the basis ofthe virtual grid characteristics and the scattered componentinformation. Therefore, the scattered X-ray removal unit 37 performs aprocess of performing frequency decomposition for the subject image Ikto acquire frequency components in a plurality of frequency bands andreducing the gain of at least one frequency component, combines theprocessed frequency component with the other frequency components, andacquires the subject image Ik subjected to the scattered X-ray removalprocess. In addition, any known method, such as wavelet transformationor Fourier transformation, may be used as the frequency decompositionmethod, in addition to a method that performs multi-resolutionconversion for the subject image Ik.

The scattered X-ray removal unit 37 calculates a conversion coefficientR(x, y) for converting a frequency component from the scattered X-raytransmissivity Ts and the primary X-ray transmissivity Tp which are thevirtual grid characteristics, and the scattered X-ray contentdistribution S(x, y), using the following Expression (16).

R(x, y)=S(x, y)×Ts+(1−S(x, y))×Tp   (16)

Since the scattered X-ray transmissivity Ts, the primary X-raytransmissivity Tp, and the scattered X-ray content distribution S(x, y)have a value in the range of 0 to 1, the conversion coefficient R(x, y)also has a value in the range of 0 to 1. The scattered X-ray removalunit 37 calculates the conversion coefficient R(x, y) for each of aplurality of frequency bands.

In the following description, it is assumed that the pixel value of thesubject image Ik is represented by Ik(x, y), a frequency component imageobtained by frequency decomposition is represented by Ik(x, y, r),frequency synthesis is represented by Ik(x, y)=ΣrIk(x, y, r), aconversion coefficient for each frequency band is represented by R(x, y,r), and scattered X-ray transmissivity and primary X-ray transmissivityfor each frequency band are represented by Ts(r) and Tp(r),respectively. In addition, it is assumed that “r” indicates the layer ofthe frequency band and the frequency decreases as “r” increases.Therefore, Ik(x, y, r) is a frequency component image in a certainfrequency band. It is preferable to use the scattered X-ray contentdistribution S(x, y) of the subject image Ik without any change.Similarly to the scattered X-ray transmissivity Ts and the primary X-raytransmissivity Tp, the scattered X-ray content distribution S(x, y) maybe acquired for each frequency band.

In the third embodiment, the conversion coefficient R(x, y, r) iscalculated for each frequency component, the frequency component imageIk(x, y, r) is multiplied by the conversion coefficient R(x, y, r) of acorresponding frequency band to convert the pixel value of the frequencycomponent image Ik(x, y, r), and frequency synthesis is performed forthe frequency component image Ik(x, y, r) multiplied by the conversioncoefficient R(x, y, r) (that is, Ik(x, y, r)×R(x, y, r)) to acquire aprocessed subject image Ik′(x, y). Therefore, the process performed bythe scattered X-ray removal unit 37 is represented by the followingExpression (17). Since the conversion coefficient R(x, y, r) has a valuein the range of 0 to 1, the frequency component Ik(x, y, r) ismultiplied by the conversion coefficient R(x, y, r) of a correspondingfrequency band to reduce the pixel value at the pixel position (x, y),that is, the gain of the frequency component.

$\begin{matrix}\begin{matrix}{{{Ik}^{\prime}\left( {x,y} \right)} = {\sum{r\left\{ {{{Ik}\left( {x,y,r} \right)} \times {R\left( {x,y,r} \right)}} \right\}}}} \\{= {\sum{r\left\{ {{{Ik}\left( {x,y,r} \right)} \times \left( {{{S\left( {x,y} \right)} \times {{Ts}(r)}} +} \right.} \right.}}} \\\left. \left. {\left( {1 - {S\left( {x,y} \right)}} \right) \times {{Tp}(r)}} \right) \right\}\end{matrix} & (17)\end{matrix}$

In the third embodiment, it is assumed that the subject image Ik isdecomposed into six frequency bands and the scattered X-raytransmissivity Ts and the primary X-ray transmissivity Tp are acquiredfor six frequency bands. In this case, the scattered X-raytransmissivity Ts and the primary X-ray transmissivity Tp have valuesrepresented by, for example, the following Expression (18). InExpression (18), it is assumed that the value of the frequency band isreduced toward the right side.

Ts=(0.7, 0.7, 0.7, 0.7, 0.3, 0.2)

Tp=(0.7, 0.7, 0.7, 0.7, 0.7, 0.7)   (18)

As shown in Expression (18), the scattered X-ray transmissivity Ts andthe primary X-ray transmissivity Tp have the same value in a highfrequency band (r=1 to 4) and the scattered X-ray transmissivity Ts islower than the primary X-ray transmissivity Tp in a low frequency band(r=5 to 6). The reason is that the removal rate of the grid becomeshigher in the lower frequency band in which the frequency component ofthe scattered X-ray is dominant and the frequency dependence of theremoval rate on the primary X-ray is small.

For example, according to a subject image of the chest obtained byradiography, in the range of the mediastinal part and the lung field inwhich the content of the scattered X-ray is high, the value of theconversion coefficient calculated on the basis of Expressions (16) and(18) is large and the pixel value is largely reduced. Therefore, in theprocessed subject image Ik′ (processed image Ik′) acquired by theprocess represented by Expression (17) using the calculated conversioncoefficient, the scattered X-ray component is removed according to thetype of grid which is expected to be used.

The scattered X-ray removal unit 37 may remove the scattered X-rays ofthe subject image Ik as follows. First, similarly to the above, whenfrequency synthesis is represented by Ik(x, y)=ΣrIk(x, y, r), thescattered X-ray removal unit 37 decomposes the frequency component imageIk(x, y, r) into a scattered X-ray image (scattered X-ray component)Is(x, y, r) and a primary X-ray image (primary X-ray component) Ip(x, y,r) on the basis of the scattered X-ray content distribution S(x, y),using the following Expression (19).

Is(x, y, r)=S(x, y)×Ik(x, y, r)

Ip(x, y, r)=(1−S(x, y))×Ik(x, y, r)   (19)

The scattered X-ray removal unit 37 applies the scattered X-raytransmissivity Ts(r) and the primary X-ray transmissivity Tp(r), whichare the virtual grid characteristics, to the scattered X-ray componentIs(x, y, r) and the primary X-ray component Ip(x, y, r) to perform imageconversion and calculates a converted scattered X-ray component Is′(x,y, r) and a converted primary X-ray component Ip′(x, y, r), using thefollowing Expression (20).

Is′(x, y, r)=Is(x, y, r)×Ts(r)=(x, y)×Ik(x, y, r)×Ts(r)

Ip′(x, y, r)=Ip(x, y, r)×Tp(r)=(1−S(x, y))×Ik(x, y, r)×Tp(r)   (20)

Then, frequency synthesis is performed for the scattered X-ray componentIs′(x, y, r) and the primary X-ray component Ip′(x, y, r) to calculate aprocessed subject image Ik(x, v)′, using the following Expression (21).

$\begin{matrix}\begin{matrix}{{{Ik}^{\prime}\left( {x,y} \right)} = {\sum{r\left\{ {{{Is}^{\prime}\left( {x,y,r} \right)} + {{Ip}^{\prime}\left( {x,y,r} \right)}} \right\}}}} \\{= {\sum{r\left\{ {{{S\left( {x,y} \right)} \times {{Ik}\left( {x,y,r} \right)} \times {{Ts}(r)}} +} \right.}}} \\\left. {\left( {1 - {S\left( {x,y} \right)}} \right) \times {{Ik}\left( {x,y,r} \right)} \times {{Tp}(r)}} \right\} \\{= {\sum{r\left\{ {{{Ik}\left( {x,y,r} \right)} \times \left( {{{S\left( {x,y} \right)} \times {{Ts}(r)}} +} \right.} \right.}}} \\\left. \left. {\left( {1 - {S\left( {x,y} \right)}} \right) \times {{Tp}(r)}} \right) \right\}\end{matrix} & (21)\end{matrix}$

Next, a process performed in the third embodiment will be described.FIG. 6 is a flowchart illustrating the process performed in the thirdembodiment. When the subject image Ik acquired by the imaging device 10is input to the image analysis device 30 (S21), a process of determiningthe body thickness distribution of the subject image Ik is performed,similarly to the first embodiment (S22). S22 corresponds to the processfrom S02 to S06 illustrated in FIG. 2. Then, the characteristicacquisition unit 39 receives at least one of the grid information, thesubject information, and the imaging conditions input from the inputunit 38 (for example, the input of the grid information, S23) andacquires the virtual grid characteristic, that is, the scattered X-raytransmissivity Ts and the primary X-ray transmissivity Tp (S24).

The scattered X-ray information acquisition unit 36 analyzes the subjectimage Ik (S25) and acquires scattered X-ray component information, thatis, the scattered X-ray content distribution S(x, y) (S26). Thescattered X-ray removal unit 37 performs frequency decomposition for thesubject image Ik (S27). The process in S23 and S24, the process in S25and S26, and the process in S27 may be performed in parallel, theprocess in S25 and S26 may be performed first, or the process in S27 maybe performed first.

Then, the scattered X-ray removal unit 37 calculates the conversioncoefficient R(x, y, r) for each frequency band using Expression (16)(S28) and converts the frequency component image Ik(x, y, r) using theconversion coefficient R(x, y, r) (S29). Then, the scattered X-rayremoval unit 37 performs frequency synthesis for the converted frequencycomponent image Ik′(x, y, r) to acquire the processed image Ik′ (S30)and ends the process. The processed image Ik′ is displayed on thedisplay unit 40 and is then used for diagnosis, or it is transmitted toan external image server and is then stored therein.

As such, in the third embodiment, the image analysis device 30 includesthe scattered X-ray analysis unit 43 which performs image processing forthe subject image acquired by radiography without using the grid suchthat the same scattered X-ray removal effect as that when the subjectimage is captured actually using the grid is obtained, acquires thevirtual grid characteristics, which are the characteristics of the gridused to remove the scattered X-rays when the subject image Ik iscaptured, further acquires the scattered X-ray component information,and performs the process of removing the scattered X-rays of the subjectimage Ik on the basis of the virtual grid characteristics and thescattered X-ray component information. Therefore, the same scatteredX-ray removal effect as that obtained by the scattered X-ray removalgrid which is actually used can be given to the subject image Ik. Inaddition, the quality of the subject image Ik can be close to thequality of the subject image which is captured using various types ofscattered X-ray removal grids.

When the convergence-type grid is used, there is a concern thatconcentration unevenness will occur in the subject image Ik due to theoblique incidence of radiation. However, in the third embodiment, sincethe process of removing the scattered X-rays from the subject imagewhich is captured without using a grid is performed, concentrationunevenness due to the oblique incidence of radiation does not occur andit is possible to acquire a high-quality processed image Ik′.

Next, a fourth embodiment of the invention will be described. In thefourth embodiment, an image analysis device has the same structure asthe image analysis device according to the third embodiment and only theprocess performed by the image analysis device is different from that inthe third embodiment. Therefore, in this embodiment, the detaileddescription of the device will not be repeated. In the third embodiment,frequency decomposition is performed for the subject image Ik andfrequency synthesis is performed for the converted frequency componentimage to acquire the processed image Ik′. However, the fourth embodimentdiffers from the third embodiment in that a frequency component in thefrequency band to be removed from the subject image Ik is extracted, thescattered X-ray removal process is performed for the extracted frequencycomponent, and the processed frequency component is added to orsubtracted from the subject image Ik to acquire the processed image Ik′.

In the fourth embodiment, the scattered X-ray removal unit 37 performsthe following process. First, similarly to the third embodiment,frequency decomposition is performed for the subject image Ik to acquirethe frequency component image Ik(x, y, r) and a conversion coefficientR′(x, y, r) for removal is calculated for each frequency band by thefollowing Expression (22).

R′(x, y)=S(x, y)×(1−Ts(r))+(1−S(x, y))×1−Tp(r))   (22)

Then, a removal component ΔIk(x, y, r) for each frequency band iscalculated by the following Expression (23).

$\begin{matrix}\begin{matrix}{{\Delta \; {{Ik}\left( {x,y,r} \right)}} = {{{Ik}\left( {x,y,r} \right)} \times {R^{\prime}\left( {x,y,r} \right)}}} \\{= {{{Ik}\left( {x,y,r} \right)} \times \left\{ {{{S\left( {x,y} \right)} \times \left( {1 - {{Ts}(r)}} \right)} +} \right.}} \\\left. {\left( {1 - {S\left( {x,y} \right)}} \right) \times \left( {1 - {{Tp}(r)}} \right)} \right\}\end{matrix} & (23)\end{matrix}$

Then, frequency synthesis is performed for the removal component ΔIk(x,y, and a frequency-synthesized removal component ΣrΔIk(x, y, r) issubtracted from the subject image Ik(x, y) to acquire a processedsubject image Ik′(x, y).

$\begin{matrix}\begin{matrix}{{{Ik}^{\prime}\left( {x,y} \right)} = {{{Ik}\left( {x,y} \right)} - {\sum{r\; \Delta \; {{Ik}\left( {x,y,r} \right)}}}}} \\{= {{{Ik}\left( {x,y} \right)} - {\sum{r\left\{ {{{Ik}\left( {x,y,r} \right)} \times \left\{ {{S\left( {x,y} \right)} \times} \right.} \right.}}}} \\\left. \left. {\left( {1 - {{Ts}(r)}} \right) + {\left( {1 - {S\left( {x,y} \right)}} \right) \times \left( {1 - {{Tp}(r)}} \right)}} \right\} \right\}\end{matrix} & (24)\end{matrix}$

Next, the process performed in the fourth embodiment will be described.FIG. 7 is a flowchart illustrating the process performed in the fourthembodiment. Since the process from S31 to S37 is the same as the processfrom S21 to S27 in the third embodiment, the detailed descriptionthereof will not be repeated in this embodiment.

Subsequently to S37, the scattered X-ray removal unit 37 calculates theconversion coefficient R′(x, y, r) for removal for each frequency bandusing Expression (22) (S38) and calculates the removal component ΔIk(x,y, r) for each frequency band using Expression (23) (S39). Then, thescattered X-ray removal unit 37 performs frequency synthesis for theremoval component ΔIk(x, y, r) (S40) and subtracts thefrequency-synthesized removal component ΣrΔIk(x, y, r) from the subjectimage Ik to acquire the processed image Ik′ (S41). Then, the scatteredX-ray removal unit 37 ends the process. The processed image Ik′ isdisplayed on the display unit 40 and is then used for diagnosis, or itis transmitted to an external image server and is then stored therein.

In the fourth embodiment, the scattered X-ray removal unit 37 may removethe scattered X-ray of the subject image Ik as follows. First, similarlyto the above, when frequency decomposition is represented by Ik(x,y)=ΣrIk(x, y, r), the frequency component image Ik(x, y, r) isdecomposed into a scattered X-ray component Is(x, y, r) and a primaryX-ray component Ip(x, y, r) by Expression (19), using the scatteredX-ray content distribution S(x, y). In addition, the scattered X-rayremoval unit 37 respectively applies the scattered X-ray transmissivityTs(r) and the primary X-ray transmissivity Tp(r), which are the virtualgrid characteristics, to the scattered X-ray component Is(x, y, r) andthe primary X-ray component Ip(x, y, r) to perform image conversion andcalculates a scattered X-ray removed component ΔIs(x, y, r) and aprimary X-ray removed component ΔIp(x, y, r), using the followingExpression (25).

ΔIs(x, y, r)=Is(x, y)×(1−Ts(r))=S(x, y)×Ik(x, y)×(1−Ts(r))

ΔIp(x, y, r)=Ip(x, y)×(1−Tp(r))=(1−S(x, y))×Ik(x, y)×(1−Tp(r))   (25)

Then, the scattered X-ray removal unit 37 performs frequency synthesisfor the scattered X-ray removed component ΔIs(x, y, r) and the primaryX-ray removed component ΔIp(x, y, r) and subtracts thefrequency-synthesized scattered X-ray removed component ΣrΔIs(x, y, r)and primary X-ray removed component ΣrΔIp(x, y, r) from the subjectimage Ik to calculate a processed subject image Ik′(x, y), using thefollowing Expression (26).

Ik′(x, y)=Ik(x, y)−Σr(ΔIs(x, y, r)+ΔIp(x, y, r))   (26)

In the third and fourth embodiments, preferably, the subject image Ikhas a pixel value that is proportional to an incident dose on theradiation detector, the scattered X-ray removal process is performed fora radiation dose in a linear space, and logarithmic conversion isperformed to convert the linear space into a logarithmic linear spacethat is proportional to human vision.

In the third and fourth embodiments, the characteristic acquisition unit39 acquires the scattered X-ray transmissivity Ts and the primary X-raytransmissivity Tp as the virtual grid characteristics. However, thecharacteristic acquisition unit 39 may acquire only one of the scatteredX-ray transmissivity Ts and the primary X-ray transmissivity Tp.

In the third and fourth embodiments, the scattered X-ray removal processis performed for the subject image Ik acquired by radiography withoutusing a grid. However, the scattered X-ray removal process may beperformed for the subject image Ik acquired by radiography using a grid.In this case, a process of removing a fringe caused by the grid isperformed for the subject image and then the scattered X-ray removalprocess is performed. The scattered X-ray removal process may acquire aradiographic image (first-grid-used image) that is captured using afirst grid, which is a desired grid, acquire the virtual gridcharacteristics corresponding to a desired virtual grid, and convert theamounts of scattered X-rays and primary X-rays in the acquiredfirst-grid-used image into the amounts of scattered X-rays and primaryX-rays which correspond to the grid corresponding to the acquiredvirtual grid characteristics (the grid having the scattered X-raytransmissivity and the primary X-ray transmissivity which are theacquired virtual grid characteristics), in addition, any of the firstgrid and the grid corresponding to the virtual grid characteristics mayhave a higher scattered X-ray removal effect and these grids may bearbitrarily selected according to the purpose or circumstances. Forexample, the method disclosed in JP2012-203504A can be used as theprocess of removing the fringe caused by the grid.

In addition, the scattered X-ray removal process in the third and fourthembodiments may be performed for a processed image obtained by applyingone virtual grid characteristic (first virtual grid characteristic) tothe subject image which is captured without using a grid and byperforming the scattered X-ray removal process for the subject image. Inthis case, the first virtual grid characteristic and a first processedimage that is a processed image to which the first virtual gridcharacteristic has been applied may he acquired and a second virtualgrid characteristic which corresponds to a desired virtual grid and isdifferent from the first virtual grid characteristic may be acquired.Then, the amounts of scattered X-rays and primary X-rays in the firstprocessed image may be converted into the amounts of scattered X-raysand primary X-rays corresponding to the second virtual gridcharacteristic on the basis of the second virtual grid characteristic.In addition, any of the first virtual grid characteristic and the secondvirtual grid characteristic may have a higher scattered X-ray removaleffect and these characteristics may be arbitrarily selected accordingto the purpose or circumstances.

On the basis of the subject image which is captured using a grid with agrid ratio of 3:1 (or the first processed image obtained by performingthe scattered X-ray removal process for the subject image capturedwithout using a grid, on the basis of the first virtual gridcharacteristic), a processed image that seems to be captured using agrid with a grid ratio of 10:1 which is different from the grid used canbe virtually acquired by the above-mentioned process. Conversely, on thebasis of the subject image which is captured using the grid with a gridratio of 10:1 (or the first processed image obtained by performing thescattered X-ray removal process for the subject image captured withoutusing a grid, on the basis of the first virtual grid characteristic), aprocessed image that seems to be captured using the grid with a gridratio of 3:1 which is different from the grid used can be virtuallyacquired by the above-mentioned process. In these cases, even when theradiographic image of the subject is repeatedly captured, it is possibleto easily acquire a radiographic image with a converted grid ratio.Therefore, the processed image subjected to the scattered X-ray removalprocess using a grid with a desired grid ratio can be acquired from thesubject image which is captured using a grid with an unintended gridratio or the first processed image. As a result, it is possible to meetthe demand for observing the processed image subjected to the scatteredX-ray removal process at different levels, without capturing theradiographic image of the subject again.

As a detailed method, for example, in the third embodiment, a table inwhich Sσ indicating the characteristics of scattering in Expression (14)is associated with each combination of before-conversion gridinformation corresponding to the grid before conversion andafter-conversion grid information corresponding to the grid afterconversion is stored in the storage unit 42. In addition, it is assumedthat Sc in the table is experimentally calculated in advance so as torelatively convert the characteristics of scattering caused by the gridbefore conversion into the characteristics of scattering caused by thegrid after conversion. Then, the scattered X-ray information acquisitionunit 36 acquires first grid information corresponding to the grid thatis actually used (or the virtual grid) as the before-conversion gridinformation, acquires second grid information corresponding to thedesired virtual grid as the after-conversion grid information, andacquires Sc corresponding to the first grid information and the secondgrid information on the basis of the table. Then, the scattered X-rayinformation acquisition unit 36 sets Io(x, y) to, for example, 1 andcalculates the primary X-ray image Ip(x, y) and the scattered X-rayimage Is(x, y) on the basis of the acquired So, using Expression (13)and Expression (14). Then, the scattered X-ray information acquisitionunit 36 may calculate the scattered X-ray content distribution S(x, y)on the basis of the calculated primary X-ray image Ip(x, y) andscattered X-ray image Is(x, y), using Expression (15).

In addition, the scattered X-ray removal unit 37 may perform thescattered X-ray removal process as follows. The scattered X-ray removalunit 37 acquires the first grid characteristic (primary X-raytransmissivity Tp1 and scattered X-ray transmissivity Ts1) correspondingto the grid (or the virtual grid) which is actually used and the secondvirtual grid characteristic (primary X-ray transmissivity Tp2 andscattered X-ray transmissivity Ts2) corresponding to a desired virtualgrid, for the scattered X-ray transmissivity is and the primary X-raytransmissivity Tp for each frequency band represented by Expression(18). In addition, the scattered X-ray removal unit 37 acquires Tp2/Tp1as the primary X-ray transmissivity Tp represented by Expression (18)and Ts2/Ts1. as the scattered X-ray transmissivity Ts represented byExpression (18), in order to relatively convert the characteristics ofscattering due to the first grid before conversion into thecharacteristics of scattering due to the second grid after conversion.Then, the scattered X-ray removal unit 37 applies the acquired scatteredX-ray transmissivity Ts (=Ts2/Ts1) and primary X-ray transmissivity Tp(=Tp2/Tp1) to Expression (16) to calculate the conversion coefficient Rand performs the scattered X-ray removal process using the conversioncoefficient R, similarly to the third embodiment. In Expression (16), insome cases, the conversion coefficient R(x, y) has a value greater than1 when the scattered X-ray transmissivity Ts2, which is the second gridcharacteristic, is higher than the scattered X-ray transmissivity Ts1,which is the first grid characteristic.

The first grid characteristic and the second grid characteristic may beacquired by any method. For example, a table in which the gridcharacteristics (the primary X-ray transmissivity Tp and the scatteredX-ray transmissivity Ts) that are experimentally calculated in advanceare associated with each grid information item may be prepared andstored in the storage unit 42. Then, the scattered X-ray removal unit 37may acquire the first and second grid information items and acquire thefirst and second grid characteristics corresponding to the first andsecond grid information items on the basis of the table. In addition,the first and second grid characteristics may be acquired on the basisof the user's input from the input unit 38. The grid information may beacquired by an input from the input unit 38. For example, as describedin JP2003-260053A, protrusions corresponding to the type of grid may beformed on the grid and then detected to acquire the grid information.

There is a demand for image observation using the subject image whichhas been captured without using a scattered X-ray removal grid,depending on the part to be subjected to radiography. It is notpreferable to perform the scattered X-ray removal process according tothe third and fourth embodiments for the subject image obtained bycapturing the radiographic image of the part. Therefore, it ispreferable to switch the turn-on and turn-off of the scattered X-rayremoval process according to the third embodiment, according to the partto be subjected to radiography. Information about the part to besubjected to radiography may be input from the operator or may beautomatically acquired from a radiography request input from a knownconsole PC (not illustrated) which controls the flow of radiography, orthe system may use information which is stored so as to be associatedwith the subject image as the information about the part to be subjectedto radiography after radiography. When it is difficult to acquire theinformation, a part recognition process may be performed for the subjectimage to acquire the information. In this case, a table in which theturn-on and turn-off of the process are associated with each part may bestored in the storage unit 42 and the process may be turned on or offwith reference to the table.

In the third and fourth embodiments, both the processed image Ik′ andthe subject image Ik before processing may be displayed and any one ofthe subject image Ik to be used for diagnosis may be selected.

In some cases, the previous subject image is used to perform comparativeobservation over time in order to checks the state of progress ortreatment of disease. In this case, when the subject image (referred toas a first subject image) which is captured without using the scatteredX-ray removal grid is compared with the subject image (referred to as asecond subject image) which is captured using the scattered X-rayremoval grid, it is preferable to correct the conditions of thescattered X-ray removal process according to the third or fourthembodiment, on the basis of processing conditions when a process ofremoving fringes caused by the grid is performed for the first subjectimage, such that the qualities of the first and second subject imagesare equal to each other.

A series of processes (S22 in FIG. 6 and S32 in FIG. 7) for determiningthe body thickness distribution of the subject image Ik in the third andfourth embodiments may be any process (a body thickness distributiondetermination process according to the invention) for determining thebody thickness distribution Tk of the subject K as long as it includesat least the following processes: the process of the virtual modelacquisition unit 32 acquiring a virtual model of the subject having apredetermined body thickness distribution; the process of the estimatedimage generation unit 33 generating a composite image of the estimatedprimary X-ray image, which is obtained by estimating the primary X-rayimage of the virtual model obtained by radiography from the virtualmodel, and the estimated scattered X-ray image, which is obtained byestimating the scattered X-ray image of the virtual model obtained byradiography from the virtual model, as an estimated image which isobtained by estimating the subject image of the subject obtained byradiography; the process of the correction unit 34 correcting the bodythickness distribution of the virtual model such that the differencebetween the estimated image and the subject image is reduced; and theprocess of the body thickness distribution determination unit 35determining the corrected body thickness distribution of the virtualmodel as the body thickness distribution of the subject. For example, aseries of processes (S22 in FIG. 6 and S32 in FIG. 7) for determiningthe body thickness distribution may include the processes correspondingto the second embodiment. In addition, a series of processes (S22 inFIG. 6 and S32 in FIG. 7) for determining the body thicknessdistribution of the subject image Ik in the third and fourth embodimentsmay be performed at any time as long as it is performed before theprocess of the scattered X-ray information acquisition unit 36calculating the primary X-ray image and the scattered X-ray image fromthe body thickness distribution Tk(x, y) of the subject K, on the basisof Expressions (13) and (14).

In a case in which a series of processes (see S02 to S06 in FIG. 2) fordetermining the body thickness distribution of the subject imageaccording to the invention is performed after the subject image Ik isacquired, other desired image processing, such as the scattered X-rayremoval process, is performed to generate a processed image using thedetermined body thickness distribution of the subject image, and theprocessed image is displayed, it is preferable to minimize the timerequired from the acquisition of the subject image to the display of theprocessed image (the time from the acquisition of the subject image tothe display of the processed image obtained by the process ofdetermining the body thickness distribution of the subject image andother desired image processing such as the scattered X-ray removalprocess for the subject image). For this purpose, in a series ofprocesses for determining the body thickness distribution of the subjectimage in each of the above-described embodiments, the image acquisitionunit 31 may reduce the subject image to a predetermined size to generatea reduced image and acquire the reduced image, the virtual modelacquisition unit 32 may acquire a virtual model with a sizecorresponding to the reduced image, the estimated image generation unit33 may generate an estimated image with a size corresponding to thereduced image, the correction unit 34 may correct the body thicknessdistribution of the virtual model such that the difference between theestimated image and the reduced image is reduced, and the body thicknessdistribution determination unit 35 may determine the corrected bodythickness distribution of the virtual model as the body thicknessdistribution of the subject which is enlarged to a desired size such asthe size of the subject image Ik. In this case, the processing load ofat least one process (particularly, for example, the process of theestimated image generation unit 33 generating the estimated image with asize corresponding to the reduced image and the process of thecorrection unit 34 correcting the body thickness distribution of thevirtual model such that the difference between the estimated image andthe reduced image is reduced) included in the processes for determiningthe body thickness distribution of the subject image is likely to bereduced. In addition, the time from the acquisition of the subject imageto the display of the processed image is reduced and the waiting time ofthe user is reduced. Therefore, it is possible to assist the efficientobservation operation of the user. In addition, the above-mentionedeffect is very large and it is possible to significantly reduce theoperation time of the user in a situation in which, in medicalfacilities, a plurality of subject images of a plurality of subjectsobtained by radiography are acquired, desired image processing, such asthe process of determining the body thickness distribution of thesubject image and the scattered X-ray removal process according to eachof the above-described embodiments, is sequentially performed for eachof the plurality of subject images, and the obtained processed imagesare sequentially displayed such that the user observes the processedimages. In addition, it is preferable to minimize the resolution of thereduced image in the range in which a resolution capable ofappropriately determining similarity using characteristic informationacquired from the reduced image and the characteristic information ofthe model image is maintained. Specifically, a compression ratio may bechanged in the range in which a characteristic and representative organor tissue can be identified and a model can be selected for each part ofwhich an image will be captured.

For example, in the case in which, in medical facilities, a plurality ofsubject images of a plurality of subjects obtained by radiography areacquired, desired image processing, such as the process (for example,see S02 to S06 in FIG. 2) of determining the body thickness distributionof the subject image and the scattered X-ray removal process accordingto the invention, is sequentially performed for each of the plurality ofsubject images, and the obtained processed images are sequentiallydisplayed such that the user observes the processed images, it ispreferable to effectively use the time from the acquisition of thesubject image to the display of the processed image. For example, it isconsidered that reference information for image observation is displayedbefore the display of the processed image for the time from theacquisition of the subject image to the display of the processed imageaccording to each of the above-described embodiments.

For example, as a fifth embodiment which is a modification of the imageanalysis device according to the first embodiment, after a subject imageis acquired, for the period for which a series of processes (S02 to S06in FIG. 2) for determining the body thickness distribution Tk of thesubject image Ik is performed, some or all of the following processesmay be performed: the scattered X-ray information acquisition unit 36acquires the scattered X-ray information of the subject image using apredetermined temporary body thickness distribution; and the scatteredX-ray removal unit 37 performs the scattered X-ray removal process forthe subject image Ik, on the basis of the scattered X-ray informationacquired using the temporary body thickness distribution, to generate atemporary processed image, and displays the temporary processed image onthe display unit 40 (temporary processed image generation and displayprocess).

FIG. 8 is a flowchart illustrating the fifth embodiment. An imageanalysis device according to the fifth embodiment differs from the imageanalysis device according to the first embodiment in that, for theperiod for which a series of processes (S02 to S06 in FIG. 2) fordetermining the body thickness distribution Tk of the subject image Ikis performed, the scattered X-ray information acquisition unit 36acquires scattered X-ray information indicating scattered X-raysincluded in the subject image k on the basis of a predeterminedtemporary body thickness distribution and the scattered X-ray removalunit 37 performs the scattered X-ray removal process for the subjectimage, on the basis of the scattered X-ray information acquired usingthe temporary body thickness distribution, to generate a temporaryprocessed image and displays the temporary processed image on thedisplay unit 40. For the other portions, the image analysis deviceaccording to the fifth embodiment includes the same components as theimage analysis device 30 illustrated in FIG. 1 and the functions andprocesses of each component are substantially the same as those in thefirst embodiment. Therefore, the description is focused on thedifference from the first embodiment and the description of the sameportions will not be repeated.

In the fifth embodiment, as illustrated in FIG. 8, the image acquisitionunit 31 acquires the subject image Ik, similarly to S01 in the firstembodiment (S51), performs a process (S52) of determining the bodythickness distribution Ik of the subject image Ik, similarly to thefirst embodiment (S02 to S06 in FIG. 2), acquires the scattered X-rayinformation (the primary X-ray image Ip and the scattered X-ray imageIs), using the determined body thickness distribution Tk, on the basisof Conditional Expressions (1) and (2), similarly to the optionalexample of the first embodiment, and subtracts the acquired scatteredX-ray image Is from the subject image Ik to perform the scattered X-rayremoval process (S53), similarly to the optional example of the firstembodiment.

In the fifth embodiment, when the image acquisition unit 31 acquires thesubject image (S51), the scattered X-ray information acquisition unit 36acquires a predetermined temporary body thickness distribution inparallel to the process in S52, acquires the scattered X-ray information(the primary X-ray image Ip and the scattered X-ray image Ts), using theacquired temporary body thickness distribution, on the basis ofConditional Expressions (1) and (2), similarly to the optional exampleof the first embodiment (S55), subtracts a scattered X-ray image Is′which is acquired using the temporary body thickness distribution fromthe subject image Ik, on the basis of the scattered X-ray image Is′, togenerate a temporary processed image from which the influence of thescattered X-rays has been removed, similarly to the optional example ofthe first embodiment, and stores the temporary processed image in thestorage unit 42 (S56). Then, the image analysis device 30 determineswhether the processed image obtained by the scattered X-ray removalprocess in S53 has been generated. When the processed image has not beengenerated (S57, No), the image analysis device 30 displays the temporaryprocessed image on the display unit 40 until the processed image isgenerated (S58). On the other hand, when the processed image obtained bythe process in S53 has been generated (S57, Yes), the image analysisdevice displays the processed image on the display unit 40 (S54).

According to the fifth embodiment, in a radiographic image analysisdevice which acquires the subject image Ik, performs a process ofdetermining the body thickness distribution Tk of the subject image Ik,performs desired image, processing, such as the scattered X-ray removalprocess, and displays the obtained processed image, for the period forwhich a series of processes for determining the body thicknessdistribution Tk of the subject image Ik is performed, some or all of thefollowing processes are performed: desired image processing, such as aprocess of removing the scattered X-rays of the subject image, isperformed using the predetermined temporary body thickness distribution;the processed image which is obtained using the temporary body thicknessdistribution is generated as the temporary processed image; and thetemporary processed image is displayed on the display unit 40.Therefore, the user can effectively use the time until the processedimage is displayed and observe the temporary processed image obtainedusing the temporary body thickness distribution to roughly check theregion of interest in the subject image or whether the radiographicconditions applied to the subject image are correct. Therefore, the usercan effectively perform observation and it is possible to providereference information for the user's observation.

In the fifth embodiment, the “predetermined body thickness distribution”may be any body thickness distribution which substantially correspondsto the subject K. For example, among the body thickness distributionswhich are obtained from a plurality of previous subject images by a bodythickness determination process, the latest body thickness distributioncan be used. In addition, the body thickness distribution of a standardsubject may be used.

in addition, a series of processes (S52) for determining the bodythickness distribution of the subject image Ik in the fifth embodimentmay be any process (a body thickness distribution determination processaccording to the invention) for determining the body thicknessdistribution Tk of the subject K as long as it includes at least thefollowing processes: the process of the virtual model acquisition unit32 acquiring a virtual model of the subject having a predetermined bodythickness distribution; the process of the estimated image generationunit 33 generating a composite image of the estimated primary X-rayimage, which is obtained by estimating the primary X-ray image of thevirtual model obtained by radiography from the virtual model, and theestimated scattered X-ray image, which is obtained by estimating thescattered X-ray image of the virtual model obtained by radiography fromthe virtual model, as an estimated image which is obtained by estimatingthe subject image of the subject obtained by radiography; the process ofthe correction unit 34 correcting the body thickness distribution of thevirtual model such that the difference between the estimated image andthe subject image is reduced; and the process of the body thicknessdistribution determination unit 35 determining the corrected bodythickness distribution of the virtual model as the body thicknessdistribution of the subject. For example, a series of processes (S52)for determining the body thickness distribution may include theprocesses corresponding to the second embodiment.

In the fifth embodiment, the process (S53 and S56) of removing thescattered X-rays from the subject image Ik is the same as the process ofremoving the scattered X-rays from the subject image Ik in the firstembodiment. However, any method which can remove the scattered X-raysfrom the subject image Ik can be applied. For example, in the fifthembodiment, the process (S53 and S56) of removing the scattered X-raysfrom the subject image Ik may correspond to S23 to S30 in the thirdembodiment illustrated in FIG. 6 or may correspond to S33 to S41 in thefourth embodiment illustrated in FIG. 7. In the fifth embodiment, theprocess (S53 and S54) of removing the scattered X-rays from the subjectimage Ik has been described. However, the invention is not limitedthereto. Image processing other than the scattered X-ray removal processmay be performed for the subject image Ik, or the scattered X-rayremoval process and other types of image processing may be performed forthe subject image Ik. The process from S55 to S58 can be performed forany period which partially or entirely overlaps the period of theprocess in S52 and it is preferable to early perform the process fromS55 to S58 after the subject image Ik is acquired, in order to rapidlydisplay the temporary processed image and to rapidly provide referenceinformation for the user's observation.

In each of the above-described embodiments, the process of acquiring thesubject image Ik in S01 illustrated in FIG. 2 may be performed at anytime as long as it is performed before the process of determining thedifference between the subject image and the estimated image in S04.

In the above-described embodiments, the image analysis device 30 may notinclude the scattered X-ray information acquisition unit 36 and thescattered X-ray removal unit 37 and may not perform the scattered X-rayinformation acquisition process and the scattered X-ray removal process.In this case, it is considered that the image analysis device 30 outputsthe determined body thickness distribution Tk of the subject to anotherdevice and the device performs image processing for the subject image Ikor a imaging condition determination process, using the body thicknessdistribution Tk.

The invention is not limited to the above-described embodiments and thebody thickness distribution of the subject obtained by the invention canbe used in any process for determining image processing conditionscorresponding to the body thickness of the subject for the subjectimage. For example, it is considered that the body thicknessdistribution obtained by the invention is used in, for example, agradation process of adjusting concentration or contrast, a noiseremoval process, a dynamic range adjustment process, and a frequencyemphasis process for the subject image which is a still image or amoving image. In addition, the body thickness distribution obtained bythe invention can be used in any process for determining imagingconditions corresponding to the body thickness for the subject image.When the body thickness distribution obtained by the invention is usedto determine each image processing condition or imaging conditions, anaccurate body thickness distribution is applied to the subject image andit is possible to increase the effect of improving image quality usingthe determined image processing conditions or imaging conditions.

For example, in an energy subtraction technique which acquires aradiographic image using the difference between two radiographic imagesacquired by capturing high-energy and low-energy radiations whilechanging the tube voltage, a process may be performed which determines aweight coefficient such that a large weight is given to a high-energyimage at the position where the body thickness is large when alow-energy image is subtracted from the high-energy image according tothe body thickness distribution of the subject obtained by theinvention. In this case, since an accurate body thickness distributionis applied to the subject image, it is possible to reduce the influenceof a beam hardening phenomenon in which the quality of radiation variesdepending on the thickness of the subject and to appropriately improvethe quality of the processed image.

In the field of a radiolucent image application technique or a techniquefor capturing the image of the same subject a plurality of times toacquire a plurality of radiographic images, such as a tomosynthesistechnique, it is preferable that the body thickness distribution of thesubject is acquired from the first subject image by the method accordingto the invention and the imaging conditions of the subject whose imageis to be captured are determined on the basis of the acquired bodythickness distribution. The subsequent subject image can be capturedunder appropriate imaging conditions corresponding to the bodythickness. Therefore, it is possible to improve the quality of thesubsequent subject image so as to be suitable for diagnosis.

It is preferable to store dose management information in which the bodythickness distribution of the subject obtained by the invention isassociated with the imaging conditions for each subject. The imagingconditions may include a set value which is set in, for example, theX-ray source or exposure time or may include a measured value, such as adose that is actually radiated, which is measured by, for example, adetector and exposure time. A plurality of dose management informationitems about the subject are acquired as dose history information foreach subject and the cumulative exposure of the subject at each positionfor a predetermined period of time is calculated on the basis of thedose history information. In this way, it is possible to provide usefulinformation which is a dose management index for each region indicatingwhether the cumulative exposure is equal to or greater than apredetermined threshold value beyond an allowable range in apredetermined region such as a predetermined organ. In addition, dosemanagement information about each of a plurality of different subjectscan be acquired and statistical analysis can be performed to specifywhich of the imaging conditions is used according to the tendency of thebody thickness distribution. It is possible to provide referenceinformation for determining the imaging conditions of a new subject orfor estimating the imaging conditions of the previous subject.

When two subject images forming a stereoscopic image are selected from aplurality of subject images captured by a tomosynthesis device,preferably, the body thickness distribution of the subject obtained bythe invention is acquired and two subject images are selected such thatan appropriate amount of parallax or an appropriate convergence angle(an angle formed between the imaging directions of two subject imagesforming the stereoscopic image) is obtained according to the acquiredbody thickness distribution. For example, the following process can beperformed: an index value indicating the characteristics of the bodythickness distribution, such as a maximum value, a mean, or a median, isextracted from the body thickness distribution of the subject; parallaxdetermination information which is associated with an appropriate amountof parallax (or an appropriate convergence angle) such that the amountof parallax (or the convergence angle) increases as the body thicknessof the subject increases is created for each range of the index valueand then acquired; the amount of parallax (or the convergence angle)corresponding to the index value extracted from the body thicknessdistribution of the subject is determined as the amount of parallax (orthe convergence angle) of the stereoscopic image, on the basis of theparallax determination information; and two subject images having theamount of parallax (or the convergence angle) therebetween are selectedas the subject images forming the stereoscopic image. For example, thefollowing process can be performed: an index value indicating thecharacteristics of the body thickness distribution is calculatedaccording to the body thickness distribution of the subject; thesubjects are classified into a plurality of body types, such as a thinbody type, a standard body type, and a thick body type, by the indexvalue; the amount of parallax (or the convergence angle) correspondingto the divided classification is determined as the amount of parallax ofthe stereoscopic image of the subject; and two subject images having theamount of parallax therebetween are selected as the subject imagesforming the stereoscopic image. As such, when two subject images formingthe stereoscopic image are selected from a plurality of subject images,the body thickness distribution of the subject obtained by the inventionis acquired and two subject images are appropriately selected accordingto the acquired body thickness distribution such that the amount ofparallax or the convergence angle increases as the body thicknessincreases. In this case, it is possible generate a stereoscopic imagewith a quality suitable for observation according to the body thicknessdistribution. For the amount of parallax and the convergence angle, itis possible to refer to the previous patent applications filed by theinventors (for example, JP2013-198736A, JP2013-198508A, andJP2013-154165A).

When the subject image is captured using the convergence-type grid,there is a concern that concentration unevenness occurs due to theoblique incidence of radiation. In order to prevent the occurrence ofthe concentration unevenness, the following process may be performed:the body thickness distribution obtained by the invention is acquired;when it is known that the subject in the subject image has a bilaterallysymmetric body thickness distribution as in a front image of the humanbody, it is determined whether or not the body thickness distribution issubstantially bilaterally symmetric; and when the body thicknessdistribution is not bilaterally symmetric, an image or a soundindicating that the body thickness distribution is not bilaterallysymmetric is displayed or output to prompt the operator to re-capturethe subject image. Therefore, it is possible to prevent the generationof a processed image with a quality that is not suitable for observationdue to concentration unevenness caused by the oblique incidence ofradiation.

Each of the above-described embodiments is illustrative and all of thedescriptions should not be used to interpret the technical scope of theinvention in a limited manner. The aspects of the invention are notlimited to each of the above-described embodiments (the first to fifthembodiments, other modification examples, and application examples) andthe invention includes any combination of the components according toeach embodiment and various modifications which can be made by thoseskilled in the art. That is, various additions, changes, and partialdeletions can be made, without departing from the conceptual idea andmeaning of the invention which are derived from content defined in theclaims and equivalents thereof.

In addition, for example, the system configuration, the hardwareconfiguration, the process flow, the module configuration, the userinterface, and the specific content of processing can be modified invarious ways without departing from the scope and spirit of theinvention and these modifications are also included in the technicalscope of the invention. For example, some or all of the components ofthe image analysis device may be implemented by a single workstation ormay be implemented by one or more workstations, servers, and the storagedevices which are connected to each other through a network.

In the above-described embodiments, the scattered X-ray removal processis performed using the radiographic image acquired by the imaging device10 which captures the radiographic image of the subject using theradiation detector 14. However, the invention can be applied to thestructures disclosed in JP1996-266529A (JP-H08-266529A) andJP1997-24039A (JP-H09-24039A) in which the radiographic imageinformation of the subject is stored and recorded on a storage phosphorsheet as a radiation detector and the radiographic image isphotoelectrically read from the storage phosphor sheet and is then used.

What is claimed is:
 1. A radiographic image analysis device thatanalyzes a subject image of a subject obtained by radiography toestimate a body thickness distribution of the subject, the devicecomprising: an image acquisition unit that acquires the subject image; avirtual model acquisition unit that acquires a virtual model of thesubject having a predetermined body thickness distribution; an estimatedimage generation unit that generates a composite image of an estimatedprimary X-ray image, which is obtained by estimating a primary X-rayimage of the virtual model obtained by radiography from the virtualmodel, and an estimated scattered X-ray image, which is obtained byestimating a scattered X-ray image of the virtual model obtained byradiography from the virtual model, as an estimated image which isobtained by estimating a radiographic image of the subject obtained byradiography; a correction unit that corrects the body thicknessdistribution of the virtual model such that a difference between theestimated image and the subject image is reduced; and a body thicknessdistribution determination unit that determines the corrected bodythickness distribution of the virtual model as the body thicknessdistribution of the subject.
 2. The radiographic image analysis deviceaccording to claim 1, wherein the virtual model acquisition unit furtheracquires the virtual model having the corrected body thicknessdistribution, the estimated image generation unit further generates theestimated image from the virtual model having the corrected bodythickness distribution, and the correction unit further corrects thebody thickness distribution of the virtual model such that a differencebetween the generated estimated image and the subject image is reduced.3. The radiographic image analysis device according to claim 2, wherein,when the difference between the estimated image and the subject image isequal to or less than a predetermined threshold value, the bodythickness distribution determination unit determines the body thicknessdistribution of the virtual model as the body thickness distribution ofthe subject.
 4. The radiographic image analysis device according toclaim 1, wherein the correction unit corrects the body thicknessdistribution of the virtual model such that the sum of absolute valuesof pixel values of a difference image between the estimated image andthe subject image or the sum of the squares of the pixel values of thedifference image is reduced.
 5. The radiographic image analysis deviceaccording to claim 1, wherein the correction unit changes the bodythickness distribution of the virtual model for each partial regionincluding one or more pixels in the virtual model, calculates a bodythickness of the partial region at which the difference between theestimated image and the subject image is reduced, and corrects the bodythickness distribution of the virtual model using the calculated bodythickness of each partial region.
 6. The radiographic image analysisdevice according to claim 1, wherein the predetermined body thicknessdistribution is created by acquiring a comparative subject image of acomparative subject different from the subject, which is obtained byradiography, and a three-dimensional image of the comparative subjectobtained by three-dimensional imaging, and measuring a body thickness ofthe comparative subject on a straight line corresponding to a radiationpath of the comparative subject image at each position of the acquiredthree-dimensional image.
 7. The radiographic image analysis deviceaccording to claim 1, wherein the virtual model further includescharacteristic information indicating at least one of structuresincluded in the virtual model, the arrangement of the structures, andcharacteristics of the structures with respect to radiation, and theestimated image generation unit selects a parameter for calculating theestimated image according to the structure corresponding to eachposition of the virtual model, on the basis of the characteristicinformation, and generates the estimated image.
 8. The radiographicimage analysis device according to claim 7, wherein the estimated imagegeneration unit acquires characteristic information indicatingstructures included in the subject image, the arrangement of thestructures, and characteristics of the structures with respect toradiation as the characteristic information of the virtual model,selects a parameter for calculating the estimated image according to thestructure corresponding to each position of the virtual model, on thebasis of the characteristic information, and generates the estimatedimage.
 9. The radiographic image analysis device according to claim 1,further comprising: a scattered X-ray information acquisition unit thatacquires scattered X-ray information which is obtained by estimating ascattered X-ray of the subject image, using the determined bodythickness distribution of the subject; and a scattered X-ray removalunit that performs a process of removing the scattered X-ray of thesubject image on the basis of the acquired scattered X-ray information.10. The radiographic image analysis device according to claim 1, whereinthe subject image is captured without using a scattered X-ray removalgrid.
 11. A radiographic image analysis method that is performed in aradiographic image analysis device and analyzes a subject image which isobtained by irradiating a subject with radiation to estimate a bodythickness distribution of the subject, the method comprising: an imageacquisition step of acquiring the subject image; a virtual modelacquisition step of acquiring a virtual model of the subject having apredetermined body thickness distribution; an estimated image generationstep of generating a composite image of an estimated primary X-rayimage, which is obtained by estimating a primary X-ray image of thevirtual model obtained by radiography from the virtual model, and anestimated scattered X-ray image, which is obtained by estimating ascattered X-ray image of the virtual model obtained by radiography fromthe virtual model, as an estimated image which is obtained by estimatinga radiographic image of the subject obtained by radiography; acorrection step of correcting the body thickness distribution of thevirtual model such that a difference between the estimated image and thesubject image is reduced; and a body thickness distributiondetermination step of determining the corrected body thicknessdistribution of the virtual model as the body thickness distribution ofthe subject.
 12. A non-transitory computer-readable storage mediumhaving stored therein a radiographic image analysis program thatanalyzes a subject image which is obtained by irradiating a subject withradiation to estimate a body thickness distribution of the subject, theprogram causing a computer to perform: an image acquisition step ofacquiring the subject image; a virtual model acquisition step ofacquiring a virtual model of the subject having a predetermined bodythickness distribution; an estimated image generation step of generatinga composite image of an estimated primary X-ray image, which is obtainedby estimating a primary X-ray image of the virtual model obtained byradiography from the virtual model, and an estimated scattered X-rayimage, which is obtained by estimating a scattered X-ray image of thevirtual model obtained by radiography from the virtual model, as anestimated image which is obtained by estimating a radiographic image ofthe subject obtained by radiography; a correction step of correcting thebody thickness distribution of the virtual model such that a differencebetween the estimated image and the subject image is reduced; and a bodythickness distribution determination step of determining the correctedbody thickness distribution of the virtual model as the body thicknessdistribution of the subject.